Molecular detection system for lactic acid bacteria

Abstract

The present disclosure provides methods of predicting resistance to chemotherapy and / or radiation therapy in a subject in need thereof including detecting presence of lactic acid bacteria in a sample from the subject. In some aspects, the presence of lactic acid bacteria is indicative of resistance to chemotherapy and / or radiation therapy, thereby predicting resistance to chemotherapy and / or radiation therapy in the subject.

Description

PATENT Attorney Docket No. MDA1370-1WO MOLECULAR DETECTION SYSTEM FOR LACTIC ACID BACTERIACROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority under 35 U. S. C. § 119(e) to U. S. Provisional Application No. 63 / 720,116, filed November 13, 2024. The contents of the prior application are considered part of and are hereby incorporated by reference in their entirety.INCORPORATION BY REFERENCE OF SEQUENCE LISTING

[0002] The material in the accompanying sequence listing is hereby incorporated by reference into this application. The accompanying sequence listing xml file, named MDA1370-1 WO. xml, was created on November 10, 2025, and is 3,732 bytes.BACKGROUND OF THE INVENTION FIELD OF THE INVENTION

[0003] The present invention relates generally to predicting treatment resistance in cancer, and more specifically to methods of detecting lactic acid bacteria and correlating the presence of the bacteria with treatment options in cancer.BACKGROUND INFORMATION

[0004] Tumors, even in allegedly sterile organs, have unique microbiomes that can modify treatment response and survival. While the gut microbiome indirectly affects tumor response through systemic mechanisms, including innumerable immune and metabolism-mediated pathways, tumor-resident bacteria may directly impact tumor growth, survival, and function.

[0005] There are several challenges to understanding the complex mechanisms of tumormicrobiota interactions. In preclinical models, microbiome manipulation of in vivo tumor models does not reliably recapitulate changes in the human microbiome.

[0006] In clinic, studies of the tumor microbiome are limited by longitudinal tumor biopsy availability, pitfalls of optimized sequencing and analysis protocols for formalin-embedded tumor samples, and sequencing reference libraries. Tumor strains develop in a unique environmental niches and selective pressures, and adapt or acquire additional genes and functions necessary to survive in low nutrient, low oxygen, or low pH environments. There is a need for in-depth mechanistic study of the tumor microbiome in most tumor types. Exophytic cervical cancers develop in mucosal surfaces and are amenable to repeated tumor microbiome sampling.PATENT Attorney Docket No. MDA1370-1WO SUMMARY OF THE INVENTION

[0007] The present invention is based on the seminal discovery that in cancer patients, L. iners is linked to reduced survival and resistance to chemotherapy and radiation therapy.

[0008] In certain embodiments, the present disclosure provides a method of predicting resistance to chemotherapy and / or radiation therapy in a subject in need thereof including: detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria is indicative of resistance to chemotherapy and / or radiation therapy, thereby predicting resistance to chemotherapy and / or radiation therapy in the subject.

[0009] In some aspects, the lactic acid bacteria is a L-lactate-producing lactic acid bacteria. In a particular aspect, the L-lactate-producing lactic acid bacteria is Lactobacillus iners (L. iners).

[0010] In some aspects, detecting the presence of lactic acid bacteria includes performing a polymerase chain reaction (PCR) assay on a genomic region for the lactic acid bacteria, 16S rRNA sequencing, shotgun metagenomic sequencing (SMS), T cell receptor repertoire sequencing (TCR), in situ hybridization, digital spatial profiling, deep microbiome sequencing, immune profiling, targeted bacterial culture, DNA synthesis assay, ultra-high resolution mass spectrometry (HRMS), D- / L-Lactic Acid assay, or a combination thereof.

[0011] In some aspects, detecting the presence of the lactic acid bacteria includes detecting a unique genomic region of the lactic acid bacteria.

[0012] In some aspects, detecting the unique genomic region for the lactic acid bacteria includes performing a PCR assay.

[0013] In some aspects, the PCR assay is selected from the group including quantitative PCR (qPCR), real-time PCR, rapid PCR, and multiplex PCR. In some aspects, the PCR assay is a qPCR. In some aspects, performing the qPCR assay includes using primers and a probe targeting a unique genomic region of L. iners.

[0014] In some aspects, the unique genomic region of L. iners is located within reference genome between genome coordinates 509,916 and 513,468 in reference genome CP049230.1.

[0015] In one aspect, the primers include a sequence having at least about seventeen (17) contiguous nucleotides of SEQ ID NO: 1 or SEQ ID NO:2 and which bind to the unique genomic region of L. iners.

[0016] In one aspect, the primers include SEQ ID NO: 1 and SEQ ID NO: 2.

[0017] In yet another aspect, the primers include a sequence having about fifty (50) or fewer nucleotides of SEQ ID NO:1 or SEQ ID NO:2, such as about 17 to 50 nucleotides including SEQ ID NO: 1 or 2, and which bind to the unique genomic region of L. iners.

[0018] In another aspect, the probe includes SEQ ID NO: 3.PATENT Attorney Docket No. MDA1370-1WO

[0019] In another aspect, the probe includes a sequence having at least about 17 contiguous nucleotides of SEQ ID NO:3 and which binds to the unique genomic region of L. iners.

[0020] In another aspect, the probe includes a sequence having about 50 or fewer nucleotides of SEQ ID NO:3 and which binds to the unique genomic region of L. iners.

[0021] In certain embodiments, the present disclosure provides a method of treating cancer in a subject including: detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria in the sample is indicative of a need for treatment; and optionally administering to the subject a therapeutic agent targeting the lactic acid bacteria, a metabolic product of the lactic acid bacteria and / or a cancer treatment; thereby treating cancer in the subject.

[0022] In some aspects, the cancer is selected from cervical cancer, colorectal cancer, lung cancer, head and neck cancer, or skin cancer. In some aspects, the cancer is cervical cancer.

[0023] In some aspects, the cancer treatment is chemotherapy, radiation therapy, immunotherapy, resection surgery, hormone therapy, stem cell or bone marrow transplant, or a combination thereof.

[0024] In some aspects, the therapeutic agent targeting the lactic acid bacteria is an antimicrobial therapy, a metabolic inhibitor, or a combination thereof.

[0025] In some aspects, the antimicrobial therapy comprises metronidazole, bacteriocins, lytic phages, bioengineered bacteria, probiotics, bioengineered microbial therapeutics, or a combination thereof.

[0026] In some aspects, the metabolic inhibitor is a lactate dehydrogenase (LDH) inhibitor, a monocarboxylate transporters (MCT) inhibitor, or a combination thereof.

[0027] In some aspects, the sample is tissue biopsy, plasma, saliva, tumor sample, blood sample, and / or vaginal sample. In some aspects, the sample is vaginal sample.

[0028] In certain embodiments, the present disclosure provides a kit including: primers, wherein the primers comprise a nucleic acid sequence set forth in SEQ ID NO:1 and SEQ ID NO:2, a nucleic acid probe set forth in SEQ ID NO:3; and instructions for using the primers and probe for lactic acid bacteria specific PCR on a biological sample. In one aspect, the primers and probe include sequences as few as about 17 contiguous nucleotides of SEQ ID NO:1, 2 or 3 or as many as about 50 nucleotides including SEQ ID NO:1, 2 or 3.

[0029] In some aspects, the kit described above further includes a sample collection device for obtaining the biological sample from a subject.

[0030] In some aspects, presence of lactic acid bacteria in the sample after PCR is indicative of resistance to chemotherapy and / or radiation therapy.PATENT Attorney Docket No. MDA1370-1WOBRIEF DESCRIPTION OF THE DRAWINGS

[0031] FIG. 1 is a schematic diagram showing that L. iners rewire tumor metabolism.

[0032] FIGs. 2A-2I illustrate that tumor-resident L. iners is associated with decreased recurrence-free and overall survival in cervical cancer patients. FIG. 2A illustrates a schematic diagram showing the study design and standard-of-care treatment algorithm for patients on study with number of cervical tumor swabs collected at each time point for 16S ribosomal RNA sequencing (16S). FIG. 2B illustrates a chart that shows sample types collected and available for each analysis at baseline (pre-treatment). FIG.2C illustrates a graph showing Linear discriminant analysis effect size (LEfSc) analysis of 16S data from cervical tumor swabs for bacteria enriched in non-responders to radiation in a pilot cohort (N = 41). Default parameters were used for LEfSc analysis with an LDA threshold of 4.0 for statistical significance and visualization. FIG. 2D illustrates a graph showing 16S compositional stacked bar plots of cervical tumor swabs for all patients at baseline (N = 97), sorted by vaginal community state type (CST), including L. iners, G. vaginalis, and P. bivia. FIG. 2E illustrates a graph showing Kaplan-Meier recurrence-free survival (RFS) curves stratified by presence (N = 44) or absence (n = 52) of tumoral L. iners. Survival curves censored at 24 months. Log rank test for comparison. Total # of events = 33. FIG.2F illustrates a graph that shows 16S relative counts ofL. iners in cervical tumor swabs collected during CRT. Week 1 (N = 68), week 3 (N = 66), week 5 (N = 78), and follow-up (N = 30) compared to baseline (N = 96) using paired t-tests and false discovery rate (FDR) adjusted p value. Box represents interquartile range (25th to 75th), bar indicates median, and whiskers represent minimum and maximum values. FIG. 2G illustrates a graph that shows multivariate Cox proportional hazard analysis for overall survival (OS), adjusting for gut microbiome diversity (N = 90) and tumoral L. iners (N = 90). Total # of events = 14. Square represents hazard ratio (HR) and bars represent 95% confidence intervals on HR. FIG.2H illustrates a graph showing baseline relative counts of L. iners stratified by tumor size (FIGO 2009 stage I-II [N = 54] vs. Stage III-IV [N = 47]). Unpaired t test. NS = p > 0.05. Box represents interquartile range (25th to 75th), bar indicates median, and whiskers represent minimum and maximum values. FIG. 21 illustrates a graph showing Kaplan-Meier RFS curves for patients with FIGO 2009 stage I-II tumors, stratified by presence (N = 26) or absence (n = 26) of tumoral L. iners. Survival curves censored at 54 months. Log rank test for comparison.

[0033] FIGs. 3A-3M illustrate other tumor microbiome features in pilot cohort are not associated with response or survival, related to FIG. 2A-2I. FIG. 3 A is a graph illustrating Kaplan-Meier curves for recurrence free survival stratified by baseline presence (N=38) orPATENT Attorney Docket No. MDA1370-1WO absence (N=3) of tumoral Proteobacteria in the initial cohort. Log-rank p-value reported. FIG.3B is a graph illustrating Kaplan-Meier curves for recurrence free survival stratified by baseline presence (N=23) or absence (N=18) of tumoral Gammaproteobacteria in the initial cohort. Logrank p-value reported. FIG. 3C is a graph illustrating Kaplan-Meier curves for recurrence free survival stratified by baseline presence (N=36) or absence (N=5) of tumoral Actinobacteria in the initial cohort. Log-rank p-value reported. FIG. 3D is a graph illustrating 16S Baseline tumor Simpson Diversity Index by response (Non-responders [N=12] vs. Responders [N=31]) in the initial cohort. FIG. 3E is a graph illustrating 16S Baseline tumor Pielou’s Evenness Index by response (Non-responders [N=12] vs. Responders [N=31]) in the initial cohort. FIG.3F is a graph illustrating 16S Baseline tumor Observed Features by response (Non-responders [N=12] vs. Responders [N=31]) in the initial cohort. FIG. 3G is a graph illustrating 16S Baseline tumor Faith’s Phylogenetic Diversity (PD) by response (Non-responders [N= 12] vs. Responders [N=31 ]) in the initial cohort. Comparison was made using a Wilcoxon Rank Sum test. FIG. 3H is a graph illustrating 16S Baseline tumor Fisher’s Alpha by response (Non-responders [N=12] vs. Responders [N=31]) in the initial cohort. FIG.31 is a graph illustrating Forest plot of a univariate cox proportional hazard model for recurrence-free survival with 16S baseline tumor Simpson Diversity Index (N=41) in the initial cohort. FIG. 3 J is a graph illustrating Forest plot of a univariate cox proportional hazard model for recurrence- free survival with 16S baseline tumor Pielou’s Evenness Index (N=41) in the initial cohort. FIG. 3K is a graph illustrating Forest plot of a univariate cox proportional hazard model for recurrence-free survival with 16S baseline tumor Observed Features (N=41) in the initial cohort. FIG. 3L is a graph illustrating Forest plot of a univariate cox proportional hazard model for recurrence- free survival with 16S baseline tumor Faith’s Phylogenetic Diversity (PD) (N=41) in the initial cohort. FIG. 3M is a graph illustrating Forest plot of a univariate cox proportional hazard model for recurrence-free survival with 16S baseline Fisher’s Alpha (N=41) in the initial cohort.

[0034] FIGs. 4A-4P illustrate that tumor microbiome metrics do not change significantly over time and there is no bacterial, fungal or viral surrogate for L. iners, related to Figure 1. FIG. 4 A is a box plot illustrating Simpson’s Diversity Index during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). Asterisks denote a significant p-value (<0.05).FIG. 4B is a box plot illustrating Pielou’s Evenness Index during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). Asterisks denote a significant p-value (<0.05). FIG. 4C is a box plot of Observed Features during CRT in tumor samples.PATENT Attorney Docket No. MDA1370-1WO Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). Asterisks denote a significant p-value (<0.05). FIG.4D is a box plot of Faith’s Phylogenetic Diversity (PD) during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). Asterisks denote a significant p-value (<0.05). FIG. 4E is a box plot of Firsher’s Alpha during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). Asterisks denote a significant p-value (<0.05). FIG.4F is a heatmap illustrating unsupervised hierarchical clustering of the top 25 species in baseline samples. Blue color represents low relative counts of a species while red indicates a high relative count. FIG. 4G is a box plot of relative counts of Gardnerella vaginalis during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). FIG.4H is a box plot of relative counts of Prevotella bivia during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). FIG. 41 is a box plot of relative counts of Atopobium vaginae during CRT in tumor samples. Comparisons were made using a paired t-test to compare week 1 (N=68), week 3 (N=66), week 5 (N=78), and follow-up (N=30) timepoints to baseline (N=96). FIG. 4J is Kaplan-Meier analysis for recurrence free survival stratified by baseline presence (N=55) or absence (N=41) of tumoral Gardnerella vaginalis. Logrank p-value reported. FIG. 4K is a graph illustrating Kaplan-Meier analysis for recurrence free survival stratified by baseline presence (N=45) or absence (N=50) of tumoral Prevotella bivia. Log-rank p-value reported. FIG. 4L is Kaplan-Meier analysis for recurrence free survival stratified by baseline presence (N=34) or absence (N=62) of tumoral Atopobium vaginae. Logrank p-value reported. FIG. 4M is Bar plot of baseline fungi reads per million (log normalized) by baseline L. iners status (Absent [N=69] vs. Present [N=64]). Comparison was made using an independent t-test. FIG. 4N is a bar plot of baseline fungi reads per million (log normalized) by response (Responders [N=73] vs. Non-responders [N=23]). Comparison was made using an independent t-test. FIG. 40 is bar plot of baseline total viral reads per million (log normalized) by baseline L. iners status (Absent [N=49] vs. Present [N=4]). Comparison was made using an independent t-test. FIG. 4P is a bar plot of baseline total viral reads per million (log normalized) by response (Responders [N=73] vs. Non-responders [N=23]). Comparison was made using an independent t-test.PATENT Attorney Docket No. MDA1370-1WO

[0035] FIGs. 5A-5G illustrate that gut microbiome features are significant in univariate, but not multivariate analysis, and patients with gut L. iners have tumor L. iners, related to Figure 1.

[0036] FIG. 5A is a graph illustrating multivariate cox proportional hazard analysis of overall survival including Pielou Evenness in the gut microbiome (N=90) and relative counts of baseline tumoral L. iners (N=90). FIG. 5B is a graph illustrating linear discriminant analysis effect size (LEfSc) was performed using 16S data for baseline gut bacteria associated with response (Nonresponders [N=22] vs. Responders [N=70] to CRT. Default parameters were used for LEfSc analysis with an LDA threshold of 3.0. FIG. 5C is a graph illustrating multivariate cox proportional hazard analysis of recurrence-free survival including 16S relative counts of baseline E. shigella in the gut microbiome (N=89) and relative counts of baseline tumoral L. iners (N=89). FIG. 5D is a graph illustrating Kaplan-Meier curves for recurrence-free survival stratified by baseline presence (N=71) or absence (N=21) of gut Escherichia Shigella on 16S. Log-rank p-value reported. FIG. 5E is a graph illustrating linear discriminant analysis effect size (LEfSc) was performed using 16S ribosomal RNA sequencing data for baseline gut bacteria associated with tumor L. iners status (Absent [N=48] vs. Present [N=42] to CRT. Default parameters were used for LEfSc analysis with an LDA threshold of 3.5. FIG. 5F is a graph illustrating absolute number of patients with tumoral L. iners alone (N=17) vs. gut microbiome L. iners alone (N=5) vs. both (N=25). 43 patients did not have L. iners present in their gut or tumor microbiome. FIG. 5G is a graph illustrating Kendall Rank correlation between baseline gut and tumor L. iners.

[0037] FIGs. 6A-6U illustrate that L. iners have increased T-cell infiltration and T-cells are more resilient to CRT, related to Figure 1. FIG. 6A is a graph illustrating overall productive templates in tumor samples from T-cell receptor sequencing. N=59. unpaired t-test for comparison. * p<0.05, <0.01. FIG. 6B is a graph illustrating overall tumor CD3+ cells (% lymphocytes) on flow cytometry. N=70. unpaired t-test for comparison. * p<0.05, <0.01. FIG.6C is a graph illustrating overall tumor CD4+ cells (% lymphocytes) on flow cytometry. N=70. unpaired t-test for comparison. * p<0.05, <0.01. ** p>0.01, <0.001. FIG.6D is a graph illustrating overall tumor CD8+ cells (% lymphocytes) on flow cytometry. N=70. unpaired t-test for comparison. * p<0.05, <0.01. FIG. 6E is a graph illustrating total templates over time in tumor samples from T-cell receptor sequencing L. iners + patients. N=30. paired t-test for comparison.FIG. 6F is a graph illustrating total templates over time in tumor samples from T-cell receptor sequencing in L. iners - patients. N=26. paired t-test for comparison. FIG. 6G is a graph illustrating productive clonality over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6H is a graph illustrating productivePATENT Attorney Docket No. MDA1370-1WO clonality over time in tumor samples from T-cell receptor sequencing in L. iners -patients. N=26. paired t-test for comparison. FIG. 61 is a graph illustrating productive templates over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6 J is a graph illustrating productive templates over time in tumor samples from T-cell receptor sequencing in L. iners - patients. N=26. paired t-test for comparison. FIG. 6K is a graph illustrating maximum productive frequency over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6L is a graph illustrating maximum productive frequency over time in tumor samples from T-cell receptor sequencing in L. iners - patients. N=26. paired t-test for comparison. FIG. 6M is a graph illustrating maximum frequency over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6N is a graph illustrating maximum frequency over time in tumor samples from T-cell receptor sequencing in £. iners - patients. N=26. paired t-test for comparison. FIG. 60 is a graph illustrating productive rearrangements over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG.6P is a graph illustrating productive rearrangements over time in tumor samples from T-cell receptor sequencing in L. iners - patients. N=26. paired t-test for comparison. FIG.6Q is a graph illustrating out of frame rearrangements over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6R is a graph illustrating out of frame rearrangements over time in tumor samples from T-cell receptor sequencing in £. iners - patients. N=26. paired t-test for comparison. FIG.6S is a graph illustrating productive entropy over time in tumor samples from T-cell receptor sequencing in L. iners + patients. N=30. paired t-test for comparison. FIG. 6T is a graph illustrating productive entropy over time in tumor samples from T-cell receptor sequencing in L. iners - patients. N=26. paired t-test for comparison. FIG. 6U is a graph illustrating HPV-specific TCR sequences as a proportion of total TCR sequences at each time point for L. iners+ vs. L. iners- patients. HPV-specific T-cells were identified from previously published datasets. 3 -way AN OVA for comparison.

[0038] FIGs. 7A-7N illustrate experimental data for CFS in other cell lines, related to Figure 2. FIG. 7A is a graph illustrating CaSki and Bl 188 cells treated with increasing concentrations of CFS. No statistical comparison. 20% CFS was chosen. FIG.7B is a graph illustrating cell viability of Bl 188 alone after cisplatin treatment. FIG. 7C is a graph illustrating cell viability of Bl 188 alone after irradiation (2Gy). FIG. 7D is a graph illustrating histogram of organoid size and count (percentage of total counted) for PDO Bl 188 pretreated with CC-L. iners 366 CFS, CC-L. iners 370 CFS (dark red) vs. non-cancer derived L. iners (NC-Z. iners,' pink) vs. control (NYC Broth; grey) followed by 4Gy irradiation. FIG. 7E is a graph illustrating histogram of organoid size andPATENT Attorney Docket No. MDA1370-1WO count (percentage of total counted) for PDO Bl 188 pretreated with CC-L. iners 366 CFS, CC-L. iners 370 CFS vs. non-cancer derived L. iners (NC-Z. iners) vs. control (NYC Broth) followed by 8Gy irradiation. FIG. 7F is a graph illustrating cell viability () of Ca Ski cells pretreated with CC-L. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by cisplatin. 3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7G is a graph illustrating cell viability of Ca Ski cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by gemcitabine. 3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7H is a graph illustrating cell viability of Ca Ski cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by 5 -Fluorouracil. 4 experiments, 3 replicates, 2 patient-derived CC-Z. Iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 71 is a graph illustrating cell viability of SiHa cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by cisplatin. 3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7J is a graph illustrating cell viability of SiHa cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by gemcitabine. 3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7K is a graph illustrating cell viability of SiHa cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by 5 -Fluorouracil. 2 experiments, 3 replicates, 2 patient-derived CC-Z. Iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7L is a graph illustrating Cell viability of HeLa cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by gemcitaine.3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7M is a graph illustrating cell viability of HeLa cells pretreated with CC-Z. iners cell-free supernatant (CFS) vs. NC-Z. iners CFS vs. control (NYC Broth) followed by 5-Fluorouracil. 3 experiments, 3 replicates, 2 patient-derived CC-Z. iners strains pooled. Mean and SEM are presented. One way ANOVA between each CFS and control shown. FIG. 7N is a graph illustrating HeLa cells treated with cancer-derived L. crispatus CFS, non-cancer derived L. crispatus CFS, or NYC broth control at increasing doses of irradiation. 1 experiment, 3 replicates.PATENT Attorney Docket No. MDA1370-1WO

[0039] FIGs. 8A-8P illustrate that L. iners induces treatment resistance in vitro. FIG. 8A illustrates a schematic diagram showing the workflow for the establishment and maintenance of patient-derived organoids (PDO) and Bl 88 primary cells. FIG. 8B shows illustrative imaging showing positive staining of PDOs Bl 188 with antibodies for anti-P63 and anti-Ki67, together with decreased expression of the differentiation marker staining of anti-CK13 antibody and PAS, confirming squamous carcinoma origin. Positive staining of anti-panCK marker demonstrates primary cancer cell origin. Scale bars, 100 mm. FIG. 8C illustrates images showing bright view of PDO Bl 188 pretreated with cancer-derived L. iners (CC-L. iners) cell-free supernatant (CFS) vs. control (NYC Broth) followed by 4 Gy irradiation. Scale bars, 1 mm. FIG. 8D illustrates a graph showing a histogram of organoid size and count (percentage of total counted) for organoids from PDO Bl 188 pretreated with CC-L. iners CFS vs. non-cancer-derived L. iners (NC-Z. iners) vs. control (NYC Broth) followed by 4 Gy irradiation. FIG. 8E illustrates a graph that shows cell viability of irradiated organoids from PDO Bl 188 pretreated with CC-L. iners cell-free supernatant (CFS) vs. control (NYC Broth) followed by 4 and 8 Gy irradiation. 2 experiments, 3 replicates. One way ANOVA (CFS vs. control). FIG. 8F illustrates a graph showing Bl 188 cell viability after irradiation. FIG 8G illustrates a graph showing HeLa cell viability after irradiation.FIG. 8H illustrates a graph that shows SiHa cell viability after irradiation. FIG. 81 illustrates a graph showing CaSki cell viability after irradiation. FIG.8 J B 1188 cell viability after gemcitabine (GEM) treatment. FIG. 8K illustrates a graph that shows Bl 188 cell viability after cisplatin (CIS) and 2 Gy irradiation. FIG.8L Bl 188 cell viability after 5 -fluorouracil (5-FU). FIG.8M illustrates a graph that shows Bl 188 cell viability after GEM and 2 Gy irradiation. FIG. 8N illustrates a graph that shows Bl 188 cell viability after CIS + 2 Gy irradiation. FIG. 80 illustrates a graph that shows Bl 188 cell viability after = 5-FU and 2 Gy. FIG. 8P illustrates a graph that shows Bl 188 cell viability with UV-killed bacterial fragments and IR. 1 experiment, 3 replicates. Cell viability following pretreatment of cells with control (NYC Broth), NC-L. iners CFS or CC-L. iners CFS (FIGs. 8F-8O); 3 experiments, 3 replicates each (FIGs. 8F-8O); 2 patient-derived CC-Z. iners strains pooled (FIGs. 8E-8P); one way ANOVA between CC-Z. iners with Mean and SEM are presented (FIGs. 8E-8P).

[0040] FIGs. 9A-9O illustrate that Z. iners causes treatment resistance through increased L-lactate production in the tumor microenvironment. FIG 9A illustrates a schematic diagram showing a hypothetical schematic of Z. iners production of L-lactate in the tumor microenvironment ‘ ‘priming’ ’ cervical cancer cells for lactate addiction, driving the feedback loop of lactate utilization via upregulation of GLUT1, MCT1, and MCT4, and lactate-regulated induction of reactive oxygen species signaling, HIF-1, NFkB, FGFR, ErbB3 / HER 2 / 3, and p53-PATENT Attorney Docket No. MDA1370-1WO dependent pathways. FIG 9B illustrates a graph that shows Bl 188 cells pretreated with L. iners (1 NC-Z. iners strain, 2 CC-L. iners strains) vs. control (NYC broth) CFS prior to RNA sequencing. Fold change in gene expression from control (right) to L. iners (left) is shown. Log2 (Fold Change) threshold of 1, 1. -LoglO (FDR-adjusted p value) threshold is 1.2. FIG 9C illustrates a graph showing metacore pathway analysis of significantly altered genes. Top 5 most significantly altered pathways are shown ranked by -LoglO (FDR-adjusted p value). Number above bar represents the proportion of genes altered in each pathway. FIG 9D illustrates a graph that shows L-lactate production in bacterial culture of cancer-derived CC-L. crispatus, CC-L. iners, NC-L. crispatus, NC-Z. iners, and control (NYC broth). FIG 9E illustrates a graph showing D-lactate production in bacterial culture of cancer-derived CC-L. crispatus, CC-L. iners, NC-L. crispatus, NC-Z. iners, and control (NYC broth). FIG 9F illustrates a graph that shows L-lactate levels in bacterial culture for control (NYC Broth), NC-Z. iners or CC-Z. iners. FIG 9G illustrates a graph showing L-lactate and D-lactate relative levels (g / L) for cervical tumor Cytobrush samples (log scale). N = 29. FIG 9H illustrates a graph that shows principal component analysis (PCA) of metabolites. FIG 91 illustrates a graph that shows unsupervised hierarchical clustering of most differentially abundant metabolites, grouped by metabolic process. FIG 9 J illustrates a graph that shows cell viability of pretreated Bl 188 cells with 20 mM lactate isoforms (L-lactate, D-lactate, sodium L-lactate, sodium D-lactate, media control) after irradiation (4 Gy). FIG 9K illustrates a graph that shows cell viability of pretreated Bl 188 cells with 20 mM lactate isoforms after GEM.FIG 9L illustrates a graph that shows L-lactate levels in cervical tumor Cytobrush samples before, during (week 1, week 3) and after EBRT (week 5) for Z. iners+ patients (BL N = 1; Wkl N = 6; Wk3 N = 2; Wk5 N = 4) and Z. iners- patients (BL N = 3; Wkl N = 4; Wk3 N = 6; Wk 5 N = 4).FIG 9M illustrates a graph showing D-lactate levels in cervical tumor Cytobrush samples. FIG 9N illustrates a graph that shows L-lactate levels for media control ( / ), Z. iners in culture alone (+ / ), Bl 188 cells in culture alone ( / +), vs. Bl 188 cells treated with Z. iners CFS (+ / +) for NC-Z. iners and CC-Z. iners. FIG 90 illustrates a graph showing differentially abundant metabolites present in primary cells Bl 188 treated with NYC Broth (control), NC-Z. iners (N = 1) CFS, and CC-Z. iners (N = 2) CFS, either nonirradiated (OGy) or irradiated (8 Gy), grouped by metabolic process. Unsupervised hierarchical clustering of most differentially abundant metabolites, grouped by metabolic process (FIG 91, FIG 90); Analyzed by Megazyme Kit (FIG.9D-9E), TC-MS (FIG.9L-9N) or HR-MS / IC-MS (FIG.91, FIG.90); Wilcoxon rank-sum test (FIG.9J-9M), unpaired t test with mean and SEM (FIG. 9G) or two-way AN0VA (FIG 9F) with NS p > 0.05, *p % 0.05, **p % 0.01, ***p % 0.001, ****p % 0.0001; 1 (FIG. 9B, 9F, 9J, 9N), 2 (FIG. 9H- 9J) or 3 (FIG. 9K) experiments, 3 replicates each, 2 CC-L. iners strains pooled (FIG. 9B, 9F,PATENT Attorney Docket No. MDA1370-1WO 9J); 1 experiment, 1 culture plate, no statistical comparisons (FIG. 9D-9E). Wilcoxon rank-sum test vs. CTRL unadjusted (FIG. 9J-9L) and adjusted (FIG. 9N); Comparisons for cells treated with MRS Broth (L. crispatus control), NYC Broth (L. iners control), and cancer and non-cancer derived L. iners (N = 3) and L. crispatus strains (N = 2) (FIG. 9H-9I). Normalized to unirradiated media control (FIG. 9J-9K).

[0041] FIGs. 10A-10H illustrate that L-lactate causes treatment resistance and lactate signaling pathways are upregulated, related to Figures 3 and 4. FIG. 10A is a graph illustrating Hallmark pathways for primary cells Bl 188 were pre -treated with L. iners (1 NC-Z. iners strain, 2 CC-Z. iners strains) CFS vs. control (NYC broth) prior to RNA sequencing. Fold change in gene expression from control (right) to Z. iners (left) is shown. Log2 (Fold Change) threshold of -1, 1. LoglO (FDR- adjusted p-value) threshold is 1.2. 1 experiment, 3 replicates for each group. FIG.10B is a graph illustrating cell viability of CaSki cells pretreated with lactate isoforms (20mM) prior to being treated with Gem 0.5 pM (1 experiment, 3 replicates) Unpaired t-test for comparison L-lactate to CTRL.. FIG. 10C is a graph illustrating cell viability of CaSki cells pretreated with lactate isoforms (20mM) prior to being treated with 5-FU IpM (1 experiment, 3 replicates) Unpaired t-test for comparison L-lactate to CTRL.. FIG. 10D is a graph illustrating cell viability of CaSki cells pretreated with lactate isoforms (20mM) prior to being treated with IR 3.0 gy (1 experiment, 3 replicates) Unpaired t- for comparison L-lactate to CTRL.. FIG. 10E is a graph illustrating Cell viability of primary cells Bl 188 pretreated with lactate isoforms (20mM) prior to being treated with 8 uM Cisplatin (3 experiment, 3 replicates) unpaired t-test for comparison L-lactate to CTRL. FIG. 10F is a graph illustrating Principle coordinate analysis (PC A) of nontargeted metabolomics for validation cohort. DSC p-value shown. FIG. 10G is a graph illustrating Supervised clustering of metabolites for Z. iners+ and Z. iners- tumors in validation cohort, with assigned pathways. N=29. No statistical comparison.. FIG. 10H is a graph illustrating Unsupervised clustering of metabolites for CFS alone in validation cohort, with assigned lactate regulated pathways. NS P > 0.05, *P < 0.05, ** P< 0.01, *** P < 0.001, **** P < 0.0001.

[0042] FIGs. 11A-11D illustrate that Z. mers-positivc tumors have metabolic alterations compared to Z. iners -negative tumors. FIG. 11A illustrates a graph showing principal coordinate analysis of relative abundances of tumor metabolites forZ. iners+ (N = 36) andZ. iners- tumors (N = 30). Dispersion Separability Criterion, p < 0.005. FIG. 11B illustrates a graph showing volcano plot of differentially abundant metabolites. -LoglO (adj. p value) threshold = 1.0; log2 (Fold Change) threshold 1 tol. FIG. 11C illustrates a graph that shows supervised hierarchical clustering of differentially abundant metabolites. FIG. 11D illustrates a graph that shows aPATENT Attorney Docket No. MDA1370-1WO lollipop plot of pathway assignments for differentially enriched metabolites. Sorted by effect size on a loglO scale. * FDR-adj p < 0.05. Analyzed by HR-MS and IC-MS (FIG. 11A-11D).

[0043] FIGs. 12A-12H illustrate the unique genomic features of CC-L. iners vs. NC-Z. iners maybe responsible for differing effects on cancer gene expression, related to FIG. 14A-14I. FIG.12A is a graph illustrating number of genes in Lactobacillus pangenome from Shotgun metagenome sequencing of tumor swabs, with those assigned to L. iners (blue) vs. other Lactobacilli (orange). FIG. 12B is a graph illustrating KEGG orthology molecular functions specific for cervical cancer L. iners not identified in healthy L. iners are common across different patients and associated with bacterial immunity and pathogenic phenotypes, R-M: Restrictionmodification system; PTS: PhosphoTrans ferase System; TA: Toxin-antitoxin system. FIG. 12C is a graph illustrating KEGG orthology pathways for cancer-derived L. iners are differentially identified vs. healthy L. iners. FIG. 12D is a graph illustrating fully assembled genome for one CC-L. iners isolate. FIG. 12E is a graph illustrating primary cells Bl 188 were pre-treated with NC-Z. iners CFS (1 NC-Z. iners strain) vs. CC-Z. iners CFS (2 strains) prior to RNA sequencing. Fold change in gene expression from NC-L. iners CFS (right) to CC-Z. iners CFS (left) is shown. Log2 (Fold Change) threshold of -1, 1. -LoglO (FDR-adjusted p-value) threshold is 1.2. 1 experiment, 3 replicates for each group. FIG. 12F is a graph illustrating hallmark pathways for unirradiated primary cells Bl 188 pre-treated with NC-Z. iners (1 NC-Z. iners strain) CFS vs. CC-Z. iners (2 strains) CFS prior to RNA sequencing. Fold change in gene expression from NC-L. iners (right) CFS to CC-Z. iners (left) CFS is shown. Log2 (Fold Change) threshold of -1, 1. -LoglO (FDR- adjusted p-value) threshold is 1.2. 1 experiment, 3 replicates for each group. FIG.12G is a graph illustrating hallmark pathways for irradiated (8Gy) primary cells B 1188 pre-treated with NC-Z. iners (1 NC-Z. iners strain) CFS vs. CC-Z. iners (2 strains) CFS prior to RNA sequencing. FIG. 12H is a graph illustrating hallmark pathways for irradiated (8Gy) primary cells Bl 188 pre-treated with NC-Z. iners (1 NC-Z. iners strain) CFS vs. CC-Z. iners (2 strains) CFS prior to RNA sequencing. Fold change in gene expression from NC-Z. iners (right) CFS to CC-Z. iners (left) CFS is shown. Log2 (Fold Change) threshold of-1, 1. -LoglO (FDR- adjusted p-value) threshold is 1.2. 1 experiment, 3 replicates for each group.

[0044] FIGs. 13A-13I illustrate that cancer-derived Z. iners acquires additional genes for lactate production over NC-Z. iners and alters cancer cell gene expression in pathways involved in intrinsic radiation sensitivity. FIG. 13A illustrates a diagram showing overlapping and unique genes on comparative genomic analysis for CC-Z. iners (16%) vs. NC-Z. iners (2%) vs. shared (81%). FIG. 13B illustrates a diagram that shows overlapping genes on comparative genomic analysis for healthy Z. iners vs. dyplasiaZ. iners vs. CC-Z. iners. FIG. 13C illustrates a graph thatPATENT Attorney Docket No. MDA1370-1WO shows sequential genes in pathways common to CC-L. iners and CC-L. iners (black) and unique to CC- L. iners (red) on comparative genomic analysis. LacG in CC-L. iners encodes the reversible enzyme, 6-phospho-beta-galactosidase, which converts lactose to galactose, while CC-L. iners utilizes only lactose in the lacDRA pathway. LacR is a repressor switch to turn off lactose metabolism to lactate. FIG. 13D illustrates a graph showing lollipop plot of metabolite pathways assignments for metabolites enriched in CC-L. iners isolates vs. NC-Z. iners isolates. Galactose metabolism is the only upregulated pathway, consistent with lacG gene acquisition and 6-phospho-beta-galactosidase activity. * FDR-adj p < 0.05. FIG. 13E illustrates a graph that shows top 7 differentially expressed metacore pathways for Bl 188 cells. Numbers above bars indicate significantly altered genes per pathway. FIG. 13F illustrates a graph that shows top 7 differentially expressed metacore processes for Bl 188 cells. Numbers above bars indicate significantly altered genes per pathway. FIG. 13G illustrates images showing gamma H2AX and DAPI fluorescent staining of pretreated Bl 188 cells 30 h after irradiation (8 Gy). Scale bars, 100 mm. FIG. 13H illustrates a graph that shows gamma H2AX dynamics for primary cells Bl 188 treated with 8 Gy in each CFS condition. FIG. 131 illustrates a graph showing radio-resistant EdU DNA synthesis assays for pretreated Bl 188 primary cells. Normalized to 0 Gy (black). Log2 (fold change) cutoff of 2.0 (FIG. 13E-13F); 1 independent experiment, 1 (FIG. 131) or 3 (FIG. 13E) replicates, 2 CC-L. iners strains pooled (FIG. 13E) or separate (FIG. 131); No statistical comparisons made (FIG.13H-13I).

[0045] FIGs. 14A-14I illustrate that L. iners and genomically similar, commensal, L-lactic acid-producing bacteria (LAB) portend poor prognosis across cancer types. FIG. 14A illustrates a graph that shows recurrence-free survival (RFS) for L. iners presence (N = 57) or absence (N = 990) in primary tumor samples from the non-small-cell lung carcinoma (NSCLC) TCGA dataset. Log-rank test for comparison. FIG. 14B illustrates a diagram that shows consecutive operons found in L. iners isolates and deposited genomes (CC-L. iners = 2, NC-Z. iners = 2) on comparative genomic analysis. Orange denotes lacG gene found only in CC-Z. iners isolates, vs. red which denotes lac genes found in all Z. iners isolates. FIG. 14C illustrates a chart that shows a flowchart for identification of genetically similar LAB species in TCGA datasets. FIG. 14D illustrates a graph that shows frequency of lacGDRA bacteria genomically similar to Z. iners (N = 46) across MDACC (anal, vaginal / vulvar, cervix) and TCGA datasets (head and neck, skin, colorectal, lung). Red box denotes species is present and associated with decreased RFS and / or overall survival (OS) in individual dataset. Dark gray box denotes species is present in dataset, but not associated with RFS or OS. FIG. 14E illustrates a graph that shows RFS for patients with NSCLC stratified by presence (N = 262) or absence (N = 576) of any lacGDRA species fromPATENT Attorney Docket No. MDA1370-1WO Bacterial and Viral Bioinformatics Resource Center (BV-BRC). Log-rank test for comparison.FIG. 14F RFS for patients with colorectal adenocarcinoma stratified by presence (N = 155) or absence (N = 276) of any lacGDRA species. Log-rank test for comparison. FIG. 14G RFS for patients with head and neck squamous cell carcinoma (HNSCC) stratified by presence (N = 31) or absence (N = 91) of any lacGDRA species. Log-rank test for comparison. FIG. 14H RFS for patients with HNSCC stratified by presence of at least one obligate D-lactate-producing lacGDRA bacterial species (Leptotrichia trevisanii or Leptotrichia wadei) and no obligate L-lactate-producing lacGDRA bacterial species (N = 64) vs. at least one L-lactate producing species (Lactobacillus paragasseri, Streptococcus infantis, Lactobacillus johnsonii, Streptococcus sp. oral taxon 064, or Lacticaseibacillus paracasei; N = 15). Log-rank test for comparison. FIG. 141 illustrates a graph that shows OS for patients with HNSCC stratified by presence of at least one obligate D-lactate-producing lacGDRA bacterial species (Leptotrichia trevisanii or Leptotrichia wadei) and no obligate L-lactate -producing lacGDRA bacterial species (N = 77) vs. at least one L-lactate-producing species (Lactobacillus paragasseri, Streptococcus infantis, Lactobacillus johnsonii, Streptococcus sp. oral taxon 064, or Lacticaseibacillus paracasei; N = 29). Kaplan-Meier survival curves with log rank test for comparison. (FIG. 14A, 14E-14I). Log-rank test for comparison.

[0046] FIG. 15 illustrates experimental design for L. iners qPCR PRIME-TR Assay.

[0047] FIGs. 16A-16B illustrate results of L. iners qPCR standard curves on average establish detection as low as ~30 genome copies. FIG. 16A is a graph illustrating L. iners qPCR standard curve (Prime-TR). FIG. 16B is a graph illustrating L. iners qPCR standard curve (Thermo Fisher).

[0048] FIGs. 17A-17B illustrate L. iners successfully detected and co-validated in mixed clinical cervical swab samples. FIG. 17A is a graph illustrating L. iners qPCR (Prime-TR). FIG.17B is a graph illustrating L. iners qPCR (Thermo Fisher).DETAILED DESCRIPTION OF THE INVENTION

[0049] The present invention is based on the seminal discovery that in cancer patients, L. iners is linked to reduced survival and resistance to chemotherapy and radiation therapy.

[0050] Before the present compositions and methods are described, it is to be understood that this invention is not limited to particular compositions, methods, and experimental conditions described, as such compositions, methods, and conditions may vary. It is also to be understood that the terminology used herein is for purposes of describing particular aspects only, and is not intended to be limiting, since the scope of the present invention will be limited only in the appended claims.PATENT Attorney Docket No. MDA1370-1WO

[0051] As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, references to “the method” includes one or more methods, and / or steps of the type described herein which will become apparent to those persons skilled in the art upon reading this disclosure and so forth.

[0052] As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0053] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

[0054] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the invention, it will be understood that modifications and variations are encompassed within the spirit and scope of the instant disclosure. The preferred methods and materials are now described.

[0055] Described herein is a molecular detection system for the bacterium lactic acid bacteria, starting with Lactobacillus iners (L. iners), leveraging quantitative polymerase chain reaction (qPCR) technology to target specific genomic regions unique to L. iners (NCBI Reference Sequence: WP 006737305.1). The system employs primer and probes designed to amplify a gene that codes for an ABC transporter ATP -binding protein found to be specific to L. iners. In one particular aspect of the invention, the unique genomic region of L. iners is located within reference genome between genome coordinates 509,916 and 513,468 in reference genome CP049230.1.

[0056] In certain embodiments, the present disclosure provides a method of predicting resistance to chemotherapy and / or radiation therapy in a subject in need thereof including: detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria is indicative of resistance to chemotherapy and / or radiation therapy, thereby predicting resistance to chemotherapy and / or radiation therapy in the subject.

[0057] As used herein the term “resistance to chemotherapy and / or radiation therapy” refers to when cancer cells are no longer affected by chemotherapy and / or radiation therapy and begin to grow again. Resistance to chemotherapy and / or radiation therapy can occur when cancer cells change their molecular makeup to become insensitive to treatments. This can lead to treatment failure or cancer returning, also known as recurrence or relapse. Resistance can occur in any typePATENT Attorney Docket No. MDA1370-1WO of tumor and with any treatment method and can be a major obstacle to cancer treatment. It can develop quickly, within weeks of starting treatment, or it can develop months or years later.

[0058] By chemotherapy is meant a cancer treatment that uses drugs to kill cancer cells, stop or slow their growth. Chemotherapy can be used to cure cancer, reduce the chance of it returning, or ease symptoms and are generally known to those of skill in the art. Chemotherapy can be used in conjunction with other treatments, such as radiotherapy or surgery. Chemotherapy can be administered in many ways, including orally, intravenously, or topically. The treatment can take place at home, in a hospital, or at a day clinic for example. Examples of chemotherapy include but are not limited to, Actinomycin, Azacitidine, Azathioprine, Bleomycin, Bortezomib, Carboplatin, Capecitabine, Cisplatin, Chlorambucil, Cyclophosphamide, Cytarabine, Daunorubicin, Docetaxel, Doxifluridine, Doxorubicin, Epirubicin, Epothilone, Etoposide, Fluorouracil, Gemcitabine, Hydroxyurea, Idarubicin, Imatinib, Irinotecan, Mechlorethamine, Mercaptopurine, Methotrexate, Mitoxantrone, Oxaliplatin, Paclitaxel, Pemetrexed, Teniposide, Tioguanine, Topotecan, Valrubicin, Vinblastine, Vincristine, Vindesine, Vinorelbine, panitumamab, Erbitux (cetuximab), matuzumab, IMC-IIF 8, TheraCIM hR3, denosumab, Avastin (bevacizumab), Humira (adalimumab), Herceptin (trastuzumab), Remicade (infliximab), rituximab, Synagis (palivizumab), Mylotarg (gemtuzumab oxogamicin), Raptiva (efalizumab), Tysabri (natalizumab), Zenapax (dacliximab), NeutroSpec (Technetium (99mTc) fanolesomab), tocilizumab, ProstaScint (Indium-Ill labeled Capromab Pendetide), Bexxar (tositumomab), Zevalin (ibritumomab tiuxetan (IDEC-Y2B8) conjugated to yttrium 90), Xolair (omalizumab), Mab Thera (Rituximab), ReoPro (abciximab), MabCampath (alemtuzumab), Simulect (basiliximab), LeukoScan (sulesomab), CEA-Scan (arcitumomab), Verluma (nofetumomab), Panorex (Edrecolomab), alemtuzumab, CDP 870, natalizumab Gilotrif (afatinib), Lynparza (olaparib), Perjeta (pertuzumab), Otdivo (nivolumab), Bosulif (bosutinib), Cabometyx (cabozantinib), Ogivri (trastuzumab-dkst), Sutent (sunitinib malate), Adcetris (brentuximab vedotin), Alecensa (alectinib), Calquence (acalabrutinib), Yescarta (ciloleucel), Verzenio (abemaciclib), Keytruda (pembrolizumab), Aliqopa (copanlisib), Nerlynx (neratinib), Imfinzi (durvalumab), Darzalex (daratumumab), Tecentriq (atezolizumab), Tarceva (erlotinib), nitrogen mustards, alkylsulfonates, nitrosoureas, triazines, ethylenimines, platinum drugs, genotoxic agents, all-trans retinoic acid, arsenic trioxide, asparaginase, eribulin, ixabepilone, mitotane, omacetaxine, pegaspargase, procarbazine, romidepsin, and vorinostat.

[0059] By radiation therapy or radiotherapy is meant a cancer treatment that uses radiation to kill or control the growth of cancer cells. Radiotherapy uses high doses of radiation from sources like X-rays, gamma rays, neutrons, or protons to damage and destroy cancer cells. Radiation canPATENT Attorney Docket No. MDA1370-1WO be delivered externally with a machine outside the body, or internally with radioactive material placed in the body.

[0060] The term “subject” as used herein refers to any individual or patient to which the subject methods are performed. Generally, the subject is human, although as will be appreciated by those in the art, the subject may be a non-human animal. Thus, other animals, including vertebrate such as rodents (including mice, rats, hamsters and guinea pigs), cats, dogs, rabbits, farm animals including cows, horses, goats, sheep, pigs, chickens, and non-human primates (including monkeys, chimpanzees, orangutans and gorillas) are included within the definition of subject.

[0061] The term “cancer” refers to a group diseases characterized by abnormal and uncontrolled cell proliferation starting at one site (primary site) with the potential to invade and to spread to other sites (secondary sites, metastases) which differentiate cancer (malignant tumor) from benign tumor. Virtually all the organs can be affected, leading to more than 100 types of cancer that can affect humans. Cancers can result from many causes including genetic predisposition, viral infection, exposure to ionizing radiation, exposure environmental pollutant, tobacco and or alcohol use, obesity, poor diet, lack of physical activity or any combination thereof.

[0062] Examples of cancers include but are not limited to Acute Lymphoblastic Leukemia, Adult; Acute Lymphoblastic Leukemia, Childhood; Acute Myeloid Leukemia, Adult; Adrenocortical Carcinoma; Adrenocortical Carcinoma, Childhood; AIDS-Related Lymphoma; AIDS-Related Malignancies; Anal Cancer; Astrocytoma, Childhood Cerebellar; Astrocytoma, Childhood Cerebral; Bile Duct Cancer, Extrahepatic; Bladder Cancer; Bladder Cancer, Childhood; Bone Cancer, Osteosarcoma / Malignant Fibrous Histiocytoma; Brain Stem Glioma, Childhood; Brain Tumor, Adult; Brain Tumor, Brain Stem Glioma, Childhood; Brain Tumor, Cerebellar Astrocytoma, Childhood; Brain Tumor, Cerebral Astro cytoma / Malignant Glioma, Childhood; Brain Tumor, Ependymoma, Childhood; Brain Tumor, Medulloblastoma, Childhood; Brain Tumor, Supratentorial Primitive Neuroectodermal Tumors, Childhood; Brain Tumor, Visual Pathway and Hypothalamic Glioma, Childhood; Brain Tumor, Childhood (Other); Breast Cancer; Breast Cancer and Pregnancy; Breast Cancer, Childhood; Breast Cancer, Male; Bronchial Adenomas / Carcinoids, Childhood: Carcinoid Tumor, Childhood; Carcinoid Tumor, Gastrointestinal; Carcinoma, Adrenocortical; Carcinoma, Islet Cell; Carcinoma of Unknown Primary; Central Nervous System Lymphoma, Primary; Cerebellar Astrocytoma, Childhood; Cerebral Astrocytoma / Malignant Glioma, Childhood; Cervical Cancer; Childhood Cancers; Chronic Lymphocytic Leukemia; Chronic Myelogenous Leukemia; Chronic Myeloproliferative Disorders; Clear Cell Sarcoma of Tendon Sheaths; Colon Cancer; Colorectal Cancer, Childhood; Cutaneous T-Cell Lymphoma; Endometrial Cancer; Ependymoma, Childhood; Epithelial Cancer,PATENT Attorney Docket No. MDA1370-1WO Ovarian; Esophageal Cancer; Esophageal Cancer, Childhood; Ewing's Family of Tumors; Extracranial Germ Cell Tumor, Childhood; Extragonadal Germ Cell Tumor; Extrahepatic Bile Duct Cancer; Eye Cancer, Intraocular Melanoma; Eye Cancer, Retinoblastoma; Gallbladder Cancer; Gastric (Stomach) Cancer; Gastric (Stomach) Cancer, Childhood; Gastrointestinal Carcinoid Tumor; Germ Cell Tumor, Extracranial, Childhood; Germ Cell Tumor, Extragonadal; Germ Cell Tumor, Ovarian; Gestational Trophoblastic Tumor; Glioma. Childhood Brain Stem; Glioma. Childhood Visual Pathway and Hypothalamic; Hairy Cell Leukemia; Head and Neck Cancer; Hepatocellular (Liver) Cancer, Adult (Primary); Hepatocellular (Liver) Cancer, Childhood (Primary); Hodgkin's Lymphoma, Adult; Hodgkin's Lymphoma, Childhood; Hodgkin's Lymphoma During Pregnancy; Hypopharyngeal Cancer; Hypothalamic and Visual Pathway Glioma, Childhood; Intraocular Melanoma; Islet Cell Carcinoma (Endocrine Pancreas); Kaposi's Sarcoma; Kidney Cancer; Laryngeal Cancer; Laryngeal Cancer, Childhood; Leukemia, Acute Lymphoblastic, Adult; Leukemia, Acute Lymphoblastic, Childhood; Leukemia, Acute Myeloid, Adult; Leukemia, Acute Myeloid, Childhood; Leukemia, Chronic Lymphocytic; Leukemia, Chronic Myelogenous; Leukemia, Hairy Cell; Lip and Oral Cavity Cancer; Liver Cancer, Adult (Primary); Liver Cancer, Childhood (Primary); Lung Cancer, Non-Small Cell; Lung Cancer, Small Cell; Lymphoblastic Leukemia, Adult Acute; Lymphoblastic Leukemia, Childhood Acute; Lymphocytic Leukemia, Chronic; Lymphoma, AIDS-Related; Lymphoma, Central Nervous System (Primary); Lymphoma, Cutaneous T-Cell; Lymphoma, Hodgkin's, Adult; Lymphoma, Hodgkin's; Childhood; Lymphoma, Hodgkin's During Pregnancy; Lymphoma, Non-Hodgkin’s, Adult; Lymphoma, Non-Hodgkin's, Childhood; Lymphoma, NonHodgkin's During Pregnancy; Lymphoma, Primary Central Nervous System; Macroglobulinemia, Waldenstrom’s; Male Breast Cancer; Malignant Mesothelioma, Adult; Malignant Mesothelioma, Childhood; Malignant Thymoma; Medulloblastoma, Childhood; Melanoma; Melanoma, Intraocular; Merkel Cell Carcinoma; Mesothelioma, Malignant; Metastatic Squamous Neck Cancer with Occult Primary; Multiple Endocrine Neoplasia Syndrome, Childhood; Multiple Myeloma / Plasma Cell Neoplasm; Mycosis Fungoides; Myelodysplasia Syndromes; Myelogenous Leukemia, Chronic; Myeloid Leukemia, Childhood Acute; Myeloma, Multiple; Myeloproliferative Disorders, Chronic; Nasal Cavity and Paranasal Sinus Cancer; Nasopharyngeal Cancer; Nasopharyngeal Cancer, Childhood; Neuroblastoma; Non-Hodgkin's Lymphoma, Adult; Non-Hodgkin's Lymphoma, Childhood; Non-Hodgkin's Lymphoma During Pregnancy; Non-Small Cell Lung Cancer; Oral Cancer, Childhood; Oral Cavity and Lip Cancer; Oropharyngeal Cancer; Osteosarcoma / Malignant Fibrous Histiocytoma of Bone; Ovarian Cancer, Childhood; Ovarian Epithelial Cancer; Ovarian Germ Cell Tumor; Ovarian Low MalignantPATENT Attorney Docket No. MDA1370-1WO Potential Tumor; Pancreatic Cancer; Pancreatic Cancer, Childhood', Pancreatic Cancer, Islet Cell; Paranasal Sinus and Nasal Cavity Cancer; Parathyroid Cancer; Penile Cancer; Pheochromocytoma; Pineal and Supratentorial Primitive Neuroectodermal Tumors, Childhood; Pituitary Tumor; Plasma Cell Neoplasm / Multiple Myeloma; Pleuropulmonary Blastoma; Pregnancy and Breast Cancer; Pregnancy and Hodgkin’s Lymphoma; Pregnancy and NonHodgkin’s Lymphoma; Primary Central Nervous System Lymphoma; Primary Liver Cancer, Adult; Primary Liver Cancer, Childhood; Prostate Cancer; Rectal Cancer; Renal Cell (Kidney) Cancer; Renal Cell Cancer, Childhood; Renal Pelvis and Ureter, Transitional Cell Cancer; Retinoblastoma; Rhabdomyosarcoma, Childhood; Salivary Gland Cancer; Salivary Gland Cancer, Childhood; Sarcoma, Ewing's Family of Tumors; Sarcoma, Kaposi’s; Sarcoma Osteosarcoma / Malignant Fibrous Histiocytoma of Bone; Sarcoma, Rhabdomyosarcoma, Childhood; Sarcoma, Soft Tissue, Adult; Sarcoma, Soft Tissue, Childhood; Sezary Syndrome; Skin Cancer; Skin Cancer, Childhood; Skin Cancer (Melanoma); Skin Carcinoma, Merkel Cell; Small Cell Lung Cancer; Small Intestine Cancer; Soft Tissue Sarcoma, Adult; Soft Tissue Sarcoma, Childhood; Squamous Neck Cancer with Occult Primary, Metastatic; Stomach (Gastric) Cancer; Stomach (Gastric) Cancer, Childhood; Supratentorial Primitive Neuroectodermal Tumors, Childhood; T-Cell Lymphoma, Cutaneous; Testicular Cancer; Thymoma, Childhood; Thymoma, Malignant; Thyroid Cancer; Thyroid Cancer, Childhood; Transitional Cell Cancer of the Renal Pelvis and Ureter; Trophoblastic Tumor, Gestational; Unknown Primary Site, Cancer of, Childhood; Unusual Cancers of Childhood; Ureter and Renal Pelvis, Transitional Cell Cancer; Urethral Cancer; Uterine Sarcoma; Vaginal Cancer; Visual Pathway and Hypothalamic Glioma, Childhood; Vulvar Cancer; Waldenstrom’s Macro globulinemia; and Wilms’ Tumor.

[0063] As used herein the term lactic acid bacteria refers to a group of microorganisms that produce lactic acid as a result of fermenting carbohydrates. Examples of lactic acid bacteria species include but are not limited to Lactobacillus, Sarcobacterium, Lactococcus, Streptococcus, Enterococcus, Micrococcus, Pediococcus, Tetragonococcus, Leuconostoc, Camobacterium, Fructobacillus, Oenococcus, and Weissella.

[0064] In some aspects, the lactic acid bacteria is a L-lactate-producing lactic acid bacteria. In a particular aspect, the L-lactate-producing lactic acid bacteria is Lactobacillus iners (L. iners).

[0065] L. iners is a species in the genus Lactobacillus. It is a Gram-positive, catalase-negative, facultatively anaerobic rod-shaped bacterium. L. iners (belonging to firmicutes) is one of the dominant bacteria Lactobacillus found in the vaginas of normal women.

[0066] In some aspects, detecting the presence of lactic acid bacteria includes performing a polymerase chain reaction (PCR) assay on a genomic region for the lactic acid bacteria, 16S rRNAPATENT Attorney Docket No. MDA1370-1WO sequencing, shotgun metagenomic sequencing (SMS), T cell receptor repertoire sequencing (TCR), in situ hybridization, digital spatial profiling, deep microbiome sequencing, immune profiling, targeted bacterial culture, DNA synthesis assay, ultra-high resolution mass spectrometry (HRMS), D- / L-Lactic Acid assay, or a combination thereof.

[0067] In some aspects, detecting the presence of the lactic acid bacteria includes detecting a unique genomic region of the lactic acid bacteria.

[0068] In some aspects, detecting the unique genomic region for the lactic acid bacteria includes performing a PCR assay.

[0069] In some aspects, the PCR assay is selected from the group including quantitative PCR (qPCR), real-time PCR, rapid PCR, and multiplex PCR. In some aspects, the PCR assay is a qPCR. In some aspects, performing the qPCR assay includes using primers and a probe targeting a unique genomic region of L. iners.

[0070] In some aspects, the primers include SEQ ID NO: 1 (GCACCAACTAATGCTAATATCATTT) and SEQ ID NO: 2 (TATTGACGAATAACAAGCAAGAATC). In some aspects, the probe comprises SEQ ID NO: 3 (TGCTCTTTAACGGGTATCGAATGTGCCCAG).

[0071] In certain embodiments, the present disclosure provides a method of treating cancer in a subject including: detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria in the sample is indicative of a need for treatment; and optionally administering to the subject a therapeutic agent targeting the lactic acid bacteria, a metabolic product of the lactic acid bacteria and / or a cancer treatment; thereby treating cancer in the subject.

[0072] The term “treatment” is used interchangeably herein with the term “therapeutic method” or “therapy” and refers to 1) therapeutic treatments or measures that cure, slow down, lessen symptoms of, and / or halt progression of a diagnosed pathologic conditions or disorder, and / or 2) prophylactic / preventative measures. Those in need of treatment may include individuals already having a particular medical disorder as well as those who may ultimately acquire the disorder (i.e., those needing preventive measures).

[0073] The terms “therapeutically effective amount”, “effective dose,” “therapeutically effective dose”, “effective amount,” or the like refer to that amount of the subject agent that will elicit the biological or medical response of a tissue, system, animal or human that is being sought by the researcher, veterinarian, medical doctor or other clinician. Generally, the response is either amelioration of symptoms in a patient or a desired biological outcome (e.g., treatment of thePATENT Attorney Docket No. MDA1370-1WO disease). Such amount should be sufficient to eliminate tumor cells. The effective amount can be determined as described herein.

[0074] The terms “administration of’ and or “administering” should be understood to mean providing a pharmaceutical composition in a therapeutically effective amount to the subject in need of treatment. Administration routes can be enteral, topical or parenteral. As such, administration routes include but are not limited to inhalation, otic, buccal, conjunctival, dental, endocervical, endosinusial, endotracheal, enteral, epidural, extra-amniotic, extracorporeal, hemodialysis, infiltration, interstitial, intraabdominal, intraamniotic, intraarterial, intraarticular, intrabiliary, intrabronchial, intrabursal, intracardiac, intracartilaginous, intracaudal, intracavemous, intracavitary, intracerebroventricular, intracisternal, intracorneal, intracoronal, intracoronary, intracorpous cavemaosum, intradermal, intradiscal, intraductal, intraduodenal, intradural, intraepidermal, intraesophageal, intragastric, intragingival, intrahippocampal, intraileal, intralesional, intraluminal, intralymphatic, intramedullary, intrameningeal, intramuscular, intraocular, intraovarian, intrapericardial, intraperitoneal, intrapleural, intraprostatic, intrapulmonary, intrasinal, intraspinal, intrasynovial, intratendinous, intratesticular, intrathoracic, intratubular, intratumor, intratympanic, intrauterine, intravascular, intravenous, intravenous bolus, intravenous drip, intravesical, intravitreal, intracapsular, intraorbital, intracutaneous, iontophoresis, irrigation, laryngeal, nasal, nasogastric, ophthalmic, oral, oropharyngeal, parenteral, percutaneous, periarticular, peridural, perineural, periodontal, rectal, retrobulbar, subarachnoid, subconjunctival, subcutaneous, sublingual, submucosal, topical, transdermal, transmucosal, transplacental, transtracheal, transtympanic, ureteral, urethral, vaginal, infraorbital, intraparenchymal, intrathecal, intraventricular, stereotactic administration subcuticular, intraarticulare, subcapsular, intrastemal, ocular administrations, as well infusion, and nebulization, or any combination thereof.

[0075] As used herein the term “cancer treatment” refers to any treatment that prevents or stops, or slows, the growth of cancer. Examples of anti-cancer treatment include but are not limited to chemotherapy, radiation therapy, immunotherapy, resection surgery, hormone therapy, targeted therapy, and stem cell or bone marrow transplant.

[0076] In some aspects, the lactic acid bacteria is an L-lactate-producing lactic acid bacteria. In a particular aspect, the L-lactate-producing lactic acid bacteria is Lactobacillus iners (L. iners).

[0077] In some aspects, detecting the presence of lactic acid bacteria includes performing a polymerase chain reaction (PCR) assay on a genomic region for the lactic acid bacteria, 16S rRNA sequencing, shotgun metagenomic sequencing (SMS), T cell receptor repertoire sequencing (TCR), in situ hybridization, digital spatial profiling, deep microbiome sequencing, immunePATENT Attorney Docket No. MDA1370-1WO profiling, targeted bacterial culture, DNA synthesis assay, ultra-high resolution mass spectrometry (HRMS), D- / L-Lactic Acid assay, or a combination thereof.

[0078] In some aspects, detecting the presence of the lactic acid bacteria includes detecting a unique genomic region of the lactic acid bacteria.

[0079] In some aspects, detecting the unique genomic region for the lactic acid bacteria includes performing a PCR assay.

[0080] In some aspects, the PCR assay is selected from the group including quantitative PCR (qPCR), real-time PCR, rapid PCR, and multiplex PCR. In some aspects, the PCR assay is a qPCR. In some aspects, performing the qPCR assay includes using primers and a probe targeting a unique genomic region of L. iners.

[0081] In some aspects, the primers include SEQ ID NO: 1 and SEQ ID NO: 2. In some aspects, the probe comprises SEQ ID NO: 3.

[0082] In some aspects, the cancer is selected from cervical cancer, colorectal cancer, lung cancer, head and neck cancer, or skin cancer. In some aspects, the cancer is cervical cancer.

[0083] In some aspects, the cancer treatment is chemotherapy, radiation therapy, immunotherapy, resection surgery, hormone therapy, stem cell or bone marrow transplant, or a combination thereof.

[0084] Immunotherapy is a treatment that uses substances to activate or suppress the immune system to help fight disease. Immunotherapies can be used to treat a variety of conditions, including cancer, infections, and other diseases. Immunotherapy can target and destroy proteins or receptors on cancer cells to prevent them from evading the immune system. Examples of immunotherapies include but are not limited to immune checkpoint inhibitors, T-cell transfer therapy, interleukins (IL-2, IL-7, IL-12), cytokines (Interferons, G-CSF, imiquimod), chemokines (CCL3, CCL26, CXCL7), immunomodulatory imide drugs (thalidomide and its analogues), and antibodies.

[0085] Resection surgery is a surgical procedure that removes tissue, part, or all of an organ. It can be performed for a variety of reasons, including to remove diseased or cancerous tissue, or to treat or cure a disease process.

[0086] Hormone therapy is a treatment that involves adding, blocking, or removing hormones to treat a variety of conditions including cancer. It is a cancer treatment that slows or stops the growth of cancer that uses hormones to grow. Hormone therapy is also called hormonal therapy, hormone treatment, or endocrine therapy.

[0087] As used herein the term “stem cell transplant” or “bone marrow transplant” refers to the process of replacing damaged blood cells with healthy stem cells obtained from bone marrow,PATENT Attorney Docket No. MDA1370-1WO meaning bone marrow transplant is just one type of stem cell transplant where the stem cells are specifically harvested from the bone marrow. Both are used to treat conditions like leukemia, lymphoma, and certain blood disorders by restoring healthy blood cell production.

[0088] In some aspects, the therapeutic agent targeting the lactic acid bacteria is an antimicrobial therapy, a metabolic inhibitor, or a combination thereof.

[0089] In some aspects, the antimicrobial therapy comprises metronidazole, bacteriocins, lytic phages, bioengineered bacteria, probiotics, bioengineered microbial therapeutics, or a combination thereof.

[0090] In some aspects, the metabolic inhibitor is a lactate dehydrogenase (LDH) inhibitor, a monocarboxylate transporters (MCT) inhibitor, or a combination thereof.

[0091] In some aspects, the sample is tissue biopsy, plasma, saliva, tumor sample, blood sample, and / or vaginal sample. In some aspects the sample is vaginal sample.

[0092] In certain embodiments, the present disclosure provides a kit including: primers, wherein the primers comprise a nucleic acid sequence set forth in SEQ ID NO:1 and SEQ ID NO:2, a nucleic acid probe set forth in SEQ ID NO:3; and instructions for using the primers and probe for lactic acid bacteria specific PCR on a biological sample.

[0093] In some aspects, the kit described above further includes a sample collection device for obtaining the biological sample from a subject.

[0094] In some aspects, presence of lactic acid bacteria in the sample after PCR is indicative of resistance to chemotherapy and / or radiation therapy.

[0095] In some aspects, the sample is tissue biopsy, plasma, saliva, tumor sample, blood sample, and / or vaginal sample. In some aspects, the sample is vaginal sample.

[0096] SequencesSEQ ID NO: 1: L. iners forward primer: GCACCAACTAATGCTAATATCATTT SEQ ID NO: 2: L. iners reverse primer: TATTGACGAATAACAAGCAAGAATC SEQ ID NO: 3: L. iners probe: TGCTCTTTAACGGGTATCGAATGTGCCCAG EXAMPLES

[0097] A total of 101 patients with newly diagnosed, locally advanced cervical cancerwere enrolled; 96 patients had pre -treatment samples collected prior to standard-of-care treatment (CRT; 45 Gy of external beam radiation therapy with weekly concurrent cisplatin at 40 mg / m2 and brachytherapy) (FIG.2A and 2B; Table 1). Samples were sent for 16S ribosomal RNA gene sequencing (16S), shotgun metagenome sequencing (SMS), T cell repertoire sequencing (TCR), and / or metabolomics (Table 2). 93 baseline gut microbiome samples were collected for 16SPATENT Attorney Docket No. MDA1370-1WO and / or SMS. 244 serial tumor swabs were also collected during and after treatment (1, 3, and 5 weeks of RT and 12-week follow-up).

[0098] Table 1: Patient Characteristics (N=101), related to FIG.2A-2I, FIG.8A-8P, FIG.9A-9NN(%) Median (IQRa)Institution 1324 (23.8) 45 (38 - 52)LBJb77 (76.2) 28.8 (25 - 33.4)MDACCcAge (years)RaceAsian / Black / Othei(12-9)Hispanic 45 (44.5)White 43 (42.6)BMId(kg / m2)Smoking StatusNever 62 (61.4)Former 29 (28.7)Current 10 (9.9)Histology21 (20.8)Non-squamouseSquamous 80 (79.2)LVSINo 22 (21.8)Yes 7 (6.9)Unknown 72 (71.3)FIGO 2009 Stag&54 (53.5)47 (46.5)GradeOther / Unknown 18 (17.8)1 7 (6.9)2 41 (40.6)3 35 (34.7)HPV TypeHPV 16 / 18 63 (62.4)Negative / Other 33 (32.7)Unknown 5 (4.9)Cisplatin Cycles 5 (5 - 6)Radiation Dose (Gy) 8834 (8169 - 9299)PATENT Attorney Docket No. MDA1370-1WO Antibiotic UsegNo 62 (61.4)Yes 38 (37.6)Unknown 1 (i-o)Nodal StatusNegative / Unknown 39 (38.6)Positive 62 (61.4)Tumor Dimension (cm) 5.3 (4 - 6.5)

[0099] Table 2: Availability of tumor swab samples for 16S sequencing at all timepoints, related to all Figures.Patient Baseline Week 1 Week 3 Week 5 Follow-up1 / y 7 x 72 / / / / X3 / / / / X4 / / / / X5 / / / / X6 / X X X X7 / / / / X8 / / / / X9 / / X / X10 / X X / X11 / X X X X12 / / / / X13 / / / / X14 / / / / X15 / / / / X16 / / / / X17 / / / / X18 / / / / X19 / / X X X20 / / / / X21 / X X X X22 / / / / X23 / / X / X24 / / / / X25 / X / / X26 / X / / X27 / X X / X28 / / / / X29 / / / / XPATENT Attorney Docket No. MDA1370-1WOPatient Baseline Week 1 Week 3 Week 5 Follow-up30 7 x 7 7 x31 / / / X / 32 / / / / / 33 / / X / / 34 / / / / / 35 / / / / / 36 / / X X / 37 / / / / / 38 / X X / X39 X / / / XEXAMPLE 1Study design, patient inclusion criteria and chemoradiation treatment

[0100] Patients with cervical cancer were enrolled on a University of Texas MD Anderson Cancer Center (MDACC) institutional review board (IRB) approved prospective biomarker collection study (MDACC 2014-0543, 2019-1059). All required ethical standards and approvals during the study were upheld, including, but not limited to, those set forth by the Declaration of Helsinki, Institutional Review Board (IRB) or Ethics Committees, and relevant national and international guidelines. Patients with locally advanced, non-metastatic cervical cancer planned for standard-of-care chemoradiation with curative intent were consented to the study. Patients were required to have visible cervical tumor amenable to sampling. 101 patients were enrolled from MDACC main campus and 23 from Harris Health System, Lyndon B. Johnson General Hospital Oncology Clinic (LB J) (Table 1) between September 2015 and March 2022. Patients underwent initial staging including PET / CT and MRI prior to enrollment. The majority of tumors were International Federation of Gynecologic Oncology (FIGO) 2009 stage IIB (37%). Patients with stage IB1 disease were treated with CRT due to gross nodal disease. Patients received a minimum of 45 Gy of external beam radiation therapy (EBRT) using intensity modulated-radiation therapy (IMRT) in 25 fractions over five weeks concurrently with weekly cisplatin 40 mg / m2 in 2 Gy fractions, followed by two pulsed-dose rate brachytherapy treatments at approximately week five and week seven with EBRT between brachytherapy treatments for gross nodal disease or persistent disease in the parametria to a minimum dose to gross disease of 60 Gy including brachytherapy contributions. Fused PET / CT and MRI scans were used for treatment planning. Brachytherapy was planned using 3-D volumetric planning, generally with MRI guidance in addition to CT. The week five sample was taken in the operating room during the first brachytherapy treatment. Response to radiation was monitored using clinical exams through thePATENT Attorney Docket No. MDA1370-1WO course of treatment, MRI at week five, and surveillance PET / CT + / MRI at approximately three months post-treatment. Non-response to radiation was defined as residual FDG-avidity at the time of first follow-up PET / CT. For survival analysis, any biopsy-proven recurrence identified on physical exam or follow-up imaging was coded as a recurrence event, and any recurrence or death due to any cause was coded as an overall survival event. Recurrence-free survival (RFS) time was calculated from diagnosis to first recurrence event or last known MDACC / LBJ clinic visit with physical exam and / or imaging. Overall survival (OS) time was calculated from diagnosis to last known contact with patient or tumor board vital status record.Cell lines

[0101] HeLa cells were a generous gift of the Sam Mok lab. Cells were cultured in IX MEM with 10% FBS and 1% Penicillin / Streptomycin at 37 C and 5% CO2. These cells have not been authenticated. SiHa cells were ordered from ATCC (HTB-35). SiHa cells were cultured in 1XMEM with 10% FBS and 1% Penicillin / Streptomycin at 37 C and 5% CO2. CaSki cells were ordered from ATCC (CRL-1550). CaSki cells were cultured in RPMI1640 supplemented with 10% FBS and 1% Penicillin / Streptomycin at 37 C and 5% CO2. Both SiHa and CaSki cells were authenticated through ATCC. HeLa, SiHa, and CaSki cell lines are female.Bacterial Strains

[0102] Lactobacillus iners isolates (ATCC, Pt-1 (IN366), Pt-2 (IN370)) were cultured in NYC III broth at 37 C in anaerobic conditions (10% CO2, 5% H2, nitrogen balance). Lactobacillus crispatus isolates (ATCC and Pt-3 (I012T4)) were cultured in MRS broth at 37 C in anaerobic conditions (10% CO2, 5% H2, nitrogen balance).Sample collection

[0103] Physicians collected swabs and cytobrush samples of the cervical tumor at five time points: baseline, week one (after five radiotherapy fractions), week three (10-15 fractions), week five (20-25 fractions; first brachytherapy treatment), and first follow-up (12 weeks posttreatment). Tumor swabs for microbiome sequencing were collected with an Isohelix Buccal Swab (Isohelix, DSK-50). Swabs were placed into individual collection tubes and transported at room temperature to the lab within 4 h 400 mLs of stabilization buffer (Isohelix) was added to each tube, or prefilled tubes were used when available (BFX S 1 / 05 / 50). Tubes were vortexed for 15 s and stored at 80 C until DNA extraction. DNA for TCR sequencing was extracted from tumor swabs using the Isohelix Xtreme DNA lysis kit per the manufacturer’s instructions (Isohelix, cat. #XME-50). Bacterial genomic DNA was extracted using MoBIO PowerSoil DNA Isolation Kit (Qiagen). DNA samples were stored at 20 C. Tumor cells and supernatant for metabolomics and flow cytometry were collected using Cytobrush Plus Endocervical Samplers (Cooper Surgical)PATENT Attorney Docket No. MDA1370-1WO from the tumor and immediate region using previously validated techniques. Brushes were placed into individual conical tubes and immediately transported at room temperature to the lab. In the lab, 10 mLs of sterile complete RPMI-1640 media, containing 1% penicillin-streptomycin and gentamicin antibiotics (HyClone, Corning, Lonza, respectively) and 10% fetal bovine serum (FBS, Coming), were added to each tube, which were then vortexed for 1 min to dislodge and suspend cells. When large amounts of mucus were present, 5 mLs of dithiothreitol solution (IX Hank’s balanced salt solution, 4% bovine serum albumin, 2 mM dithiothreitol; Invitrogen) were added to the cell suspensions and passed through a 70-mm cell strainer into new conical tubes. Cells were pelleted by centrifugation and resuspended in sterile complete RPMI-1640 media for counting. For flow cytometry, pellets were immediately used for flow cytometry. For metabolomics, cells were pelleted again and resuspended in sterile freeze media, composed of 90% FBS (Corning) and 10% DMSO (Sigma-Aldrich), and stored at 80 C. Two BBL CultureSwabs (BD Biosciences) were swabbed in the tumor region by a physician and transported to the lab within 30 min for downstream culturing to isolate patient Lactobacillus strains. For blood samples, 1 mL of blood was collected into 3 6-mL serum clot activator-containing vacutainers (BD Biosciences) and transported at room temperature to the lab within 4 h. Upon arrival in the lab the blood was immediately stored at 80 C until metabolomics processing. For human tissue used for organoid culture, fresh cancer tissue was obtained from a surgical resection specimen of a cervical cancer patient under the designated ethical protocol. She participated in this study under an IRB-approved protocol (2019-1059) and signed informed consent form approved by the responsible authority.16S rRNA sequencing

[0104] 16S rRNA gene sequencing was performed at the Alkek Center for Metagenomics and Microbiome Research (CMMR) at Baylor College of Medicine. 16S rRNA was sequenced using methods adapted from the methods used for the Human Microbiome Project and Earth Microbiome Project98,99 Briefly, the 16S rDNA V4 region was amplified by PCR using a 515F-806R primer pair and sequenced on the MiSeq platform (Illumina) using the 2x250 bp paired-end protocol. The primers used for amplification contain adapters for MiSeq sequencing and singleend barcodes allowing pooling and direct sequencing of PCR products. Shotgun metagenomic sequencing (SMS) For clinical isolates, DNA was isolated from Lactobacillus strains with Centra Puregene Yeast / Bact. Kit (Qiagen) following manufacturer’s instructions. For patient tumor samples, after 16Sv4 sequencing, DNA isolates from tumor swabs were sequenced with Illumina sequencers. SMS was performed by personnel of the Alkek Center for Metagenomics and Microbiome Research at Baylor College of Medicine. Whole Genome Shotgun sequencing wasPATENT Attorney Docket No. MDA1370-1WO performed on genomic bacterial DNA (gDNA), which was extracted to maximize bacterial DNA yield from specimens while keeping background amplification to a minimum.

[0105] Libraries were constructed from each sample using the KAPA Hyper Prep Kit (Kapa Biosystems, Wilmington, MA, USA) and sequenced using the Illumina HiSeqX platform with the 2 x 150 bp paired-end read protocol. Sequencing reads were derived from raw BCL files which were retrieved from the sequencer and called into fastqs by Casava v1.8.3 (Illumina). Appropriate read preparation steps, such as quality control, trimming and filtering and host DNA removal prior to further analysis were performed using an in-house pipeline (statistical analysis section).T cell receptor repertoire sequencing (TCR)

[0106] DNA isolated from tumor swabs was submitted for TCR sequencing to the Cancer Genomics Laboratory at the University of Texas MD Anderson Cancer Center (Houston, TX). Survey depth sequencing was performed using the Adaptive Biotechnologies immuno-SEQ human T cell receptor beta (hsTCRB) Kit, Version 3 (Adaptive Biotechnologies, ISK10101). Two replicates of 200 ng DNA per sample were prepared for qPCR with the V- and J-gene specific primers provided in the immunoSEQ hsTCRB kit and the QIAGEN Multiplex PCR Kit (Qiagen, catalog no. 206145). First, 31 cycles of qPCR were performed on all replicates, then, sample manifest barcodes generated with immuSEQ Analyzer and Illumina adapters were added to each PCR replicate for eight additional qPCR cycles. The libraries were purified using a bead-based system to remove residual primers, pooled at equal volume, and checked for quality control with Agilent DI 000 screen tapes to determine the size-adjusted concentration. The libraries were quantified with the Applied Biosystems QuantStudio 6 and the KAPA Biosystems library quantification kit, using manufacturer’s instructions. On the basis of the qPCR results, approximately 15 pmol / L of the pooled libraries were loaded onto the Miseq Sequencing System for a single end read which includes a 156-cycle Read 1 and a 15-cycle Index 1 read run. Raw sequences output from the Miseq were transferred to Adaptive’s immunoSEQ Data Assistant, where the data were processed to report the normalized and annotated TCRB repertoire profile for each sample.Isolation of L. iners strains from patient tumors

[0107] Culture swabs were collected from tumors and immediately placed in an anaerobic transport bag (BD 260683). Within 30 min of collection, tumor swabs were plated onto a TSA plate (BD Biosciences) and an MRS plate (Moltox) and incubated at 37 C in anaerobic conditions for 3-5 days. Bacterial growth from plates was sub-cultured until single colonies could be isolated. MALDI-TOF mass spectroscopy was used to identify the bacterial isolate species and performed according to the standard protocol described in the Bruker MALDI-TOF user manual.PATENT Attorney Docket No. MDA1370-1WO Generation of patient-derived organoids

[0108] Patient-derived organoids were generated as described by Lo ~ hmussaar et al., with several modifications. Cervical cancer tissue was mechanically minced using scalpels, followed by digestion in a dissociation mixture (1 mg / mL collagenase (Sigma) and 0.4 mg / mL Hyaluronidase (Sigma) in complete RPMI medium, supplemented with 10% FBS and 1% penicillin-strep tomycin, for 1.5 h at 37 C in a water bath shaker. The resulting cells were centrifuged down at 350g for 5 min, followed by adding 1-5 mL of Trypsin-EDTA (Gibco) supplemented with lOOug / ml DNase I (Sigma) and digesting the cell clumps for 8-10 min at 37 C waterbath shaker. The resulting cell suspensions were washed three times with AdDF+++ (Advanced DMEM / F12 supplemented with lx Glutamax, 10 Mm HEPES, and penicillinstreptomycin), and erythrocytes were lysed in Red Blood Cell Lysis Buffer (Roche). The cells and small cell clumps were embedded into Basement Membrane Extract (BME, Cultrex BME RGF type 2, Trevigen) and plated in 10 ml-volume droplets on a pre-warmed 24-well suspension culture plates and allowed to solidify at 37 C for 30 min before addition of full growth medium (AdDF+++ supplemented with 1% Noggin conditioned medium (made in-house), 10% ofRSPOl conditioned medium (made in-house), lx B27 supplement (GIBCO), 2.5 mM nicotinamide (Sigma), 1.25 mM n-Acetylcystein (Sigma), 10 mM ROCK inhibitor (Abmole), 500 nM A83-01 (Tocris), 10 mM forskolin (Bio-Techne), 25 ng / mL FGF7 (P eprotech), 100 ng / mL FGF10 (P eprotech) and 1 mM p38 inhibitor SB202190 (Sigma), 50 ng / mL EGF (Peprotech) and 100 mg / mL Primocin (InvivoGen)). For splitting, organoids were pipetted up and down 300 times using an electronic pipettor through a small-bore pipette tip to break up the BME and separateorganoids from the BME. After centrifugation, organoids were dissociated with TrypLE (Gibco) for 5 min in a cell culture incubator. The cells were pipetted up and down by 100 to break up the remaining cell clumps and organoids into single cells. The approximate splitting ratio was 1:4 every two weeks.Immunostaining and imaging of organoids

[0109] Organoids were fixed 20 min in 4% paraformaldehyde (PF A) at room tempreture followed by dehydration and paraffin embedding. Serial sections were cut as 5 mm and hydrated before staining. Sections were subjected to PAS staining following the manufacturer’s instructions or immunohistochemical staining by using overnight incubation with antibodies raised against P63 (Abeam), KI67 (Abeam), and CK13 (Abeam). The antigen retrieval was performed in citric acid solution (pH 6.0). Fluorescent images were acquired on Axio Observer microscope (Zeiss). The bright view images were taken on Cytation5 Cell Imaging Multimode Reader (Agilent). For organoids size counting, the diameter of each PDO in the image larger than 20 mm was taken in count using GEN 5 software.PATENT Attorney Docket No. MDA1370-1WO Lactobacilli treatments and cell viability assay

[0110] Bacterial strains were cultured under anaerobic conditions at 37 C and 190 rpm for 3-4 days until the cells reached a density of approximately 1 x 109 cells / mL. The cultures were centrifuged at 4000 rpm for 40 min at 20 C. The supernatants were sterile- filtered to prepare the CFS. After centrifugation, the bacterial pellets were resuspended in PBS to a final concentration of 108 / mL and killed using under UV-light for Ih. For CFS treatment, HeLa, SiHa, and CaSki cells and cervical cancer-derived primary cells were seeded into 6-well plates at 106 cells / well and left to adhere overnight. Once adhered, the cell media was changed to 20% v / v CFS and cultured at 37 C and 5% CO2 for two weeks; passages occurred once a week. After incubation, cells were seeded in 96 well plates at 1000 cells / well and allowed to adhere overnight. The cells were then treated with or without ionizing radiation and cisplatin (Sigma-Aldrich), 5 -fluorouracil (Sigma- Aldrich), gemcitabine (Selleck Chemical LLC S1149100MG), or a combination, as indicated in the figures. After all treatments, cells were allowed to grow for 4-6 days in 20% CFS v / v culture medium until the negative control wells reached approximately 75% confluence before cell viability was assessed. For PDOs, single cells were resuspended in icecold BME (Trevigen) and irradiated as indicated, and then the cells were seeded as 5 mL of BME in a U-bottom 96-well microplate. After 2-3 days, when small organoids emerged from single cells, 20% CFS diluted in full growth medium was added to the wells and incubated overnight for 16h, followed by cisplatin treatments for Ih. After all treatments, the medium was replaced with a full growth medium containing 20% v / v CFS and incubated for 14 days. The PDO in BME were then subjected to a cell viability assay. For the dead bacteria test, cervical cancer-derived primary cells were seeded into 96-well microplates and treated with irradiation or cisplatin. After washing with full growth medium, the dead bacterial pellets were diluted and added to the cells at a density of 160 CFU / cell and co-cultured with the cells for five days, followed by a cell viability assay. For HeLa, CaSki, SiHa, and cervical cancer-derived primary cells (Bl 188), a cell viability assay was performed using CellTiter-Glo according to the manufacturer’s instructions. In brief, CellTiter-Glo Reagent (Promega) was applied to the culture medium at a 1:1 ratio. The CellTiter-Glo 3D Reagent (Promega) was applied to the PDOs. The plates were shaken every 5 min and incubated for 30 min. The luminescence was measured using a PerkinElmer Victor X3 plate reader. Percent cell viability for each treatment group was calculated by normalizing luminescence readings to those of the non- treated IR or chemo group.Immunostaining

[0111] For gH2AX and panCK staining, cells were fixed in ice-cold methanol for 5 min at room temperature and washed once with phosphate buffered saline (PBS). After fixation, the cellsPATENT Attorney Docket No. MDA1370-1WO were incubated with antibody overnight in cold room. After primary antibody incubation, the cells were washed three times with PBS and incubated with Alexa Fluor 488-labeled anti-mouse IgG antibody (Invitrogen) containing DAPI for 1 h at room temperature. Finally, cells were mounted in mounting solution ProLong Gold (Invitrogen). Fluorescent images of panCK were acquired on Axio Observer microscope (Zeiss). Image acquisition of gH2AX was performed with a Cytation 5 Cell Imaging Multimode Reader. Microscopy image analyses were performed using the GEN 5 software. Nuclei were segmented using the DAPI channel and the resulting regions of interest transferred to the fluorescence channel of interest (488 for gammaH2AX). Prism 9 (GraphPad Software) was used to calculate p values based on T-test analyses. Data were considered statistically significant for p values <0.05.Bulk RNA sequencing

[0112] RNA samples were submitted to Cancer Genomics Center at The University of Texas Health Science Center at Houston. The RNA sample quality was assessed by RNA ScreenTape on a Tapestation (Agilent Technologies Inc., California, USA) and quantified by Qubit 2.0 RNA HS assay (ThermoFisher, Massachusetts, USA). Paramagnetic beads coupled with oligo d(T)25 are combined with total RNA to isolate poly(A)+ transcripts based on NEBNext Poly(A) mRNA Magnetic Isolation Module manual (New England BioLabs Inc., Massachusetts, USA). Prior to first strand synthesis, samples are randomly primed (50 d(N6) 3’ [N = A, C, G, T]) and fragmented based on manufacturer’s recommendations. The first strand is synthesized with the Protoscript II Reverse Transcriptase with a longer extension period, approximately 30 min at 42 C. All remaining steps for library construction were used according to the NEBNext Ultra II Library Prep Kit for Illumina (New England BioLabs Inc., Massachusetts, USA). Final libraries quantity was assessed by Qubit 2.0 (ThermoFisher, Massachusetts, USA) and quality was assessed by TapeStation HSD1000 ScreenTape (Agilent Technologies Inc., California, USA). Final library size was about 500 bp with an insert size of about 350 bp. Illumina 8-nt dual-indices were used. Equimolar pooling of libraries was performed based on QC values and sequenced on an Illumina [NovaSeq S4] (Illumina, California, USA) with a read length configuration of 150 PE for

[0040] M PE reads per sample (20M in each direction).Lactate isoform treatment of cell lines

[0113] Stock solutions of L-lactic acid, D-lactic acid, sodium L-lactate and sodium D-lactate were made at the same concentration, 4M. 20 mM lactic acid or lactate were used to culture the cells for two weeks. And the cells were seeded 1000 cells / well in a 96-well plate for chemoradiation treatments. After treatments, the cells were cultured in medium containing 20 mM lactic acid or lactate for 3-5 days, followed by CellTiterGlo assay.PATENT Attorney Docket No. MDA1370-1WO DNA synthesis assay

[0114] Cancer derived primary cells were cultured in either broth (control), NC-Z. Iners CFS, or CC-L. Iners CFS supplemented culture medium for 2 weeks, and then re-seeded and cultured for 1 day, followed by IR and serial timepoints of recovery. The cells were subjected to the DNA synthesis analysis using the Click-iT EdU Alexa Fluor 488 Flow Cytometry Assay Kit (Invitrogen, cat. No. Cl 0425). EdU at a final concentration of 40 mM was applied for 15 min, then cells were recovered for 60, 90, 120, 150 min and fixed and stained following the manufacturer’s instructions with the PI staining step included. Cells were analyzed on a Thermo Fisher Attune Nxt Flow Cytometer using the 488 nm BL3 filter for EdU and 638 RL2 filter for PI.Tumor and clinical isolate metabolomics

[0115] To determine the relative abundance of polar metabolites in samples, extracts were prepared and analyzed by ultra-high resolution mass spectrometry (HRMS). Metabolites were extracted using ice-cold 0.1% Ammonium hydroxide in 80 / 20 (v / v) methanol / water. Extracts were centrifuged at 17,000 g for 5 min at 4 C, and supernatants were transferred to clean tubes, followed by evaporation to dryness under nitrogen. Dried extracts were reconstituted in deionized water, and 5 mL was injected for analysis by ion chromatography (IC)-MS. IC mobile phase A (MPA; weak) was water, and mobile phase B (MPB; strong) was water containing 100 mM KOH. A Thermo Scientific Dionex ICS-5000+ system included a Thermo lonPac ASH column (4 mm particle size, 250 3 2 mm) with column compartment kept at 30 C. The autosampler tray was chilled to 4 C. The mobile phase flow rate was 350 mL / min and gradient from 1 mM to 100 mM KOH was used. The total run time was 60 min. To assist the desolvation for better sensitivity, methanol was delivered by an external pump and combined with the eluent via a low dead volume mixing tee. Data were acquired using a Thermo Orbitrap Fusion Tribrid Mass Spectrometer under ESI negative ionization mode at a resolution of 240,000.Analysis of D / L-Lactate levels

[0116] For rapid, quantitative analysis of D / L lactate levels in bacterial culture, the Megazyme (Neogen) D- / L-Lactic Acid (D- / L-Lactate) (Rapid) Assay Kit was used according to manufacturer instructions with spectrophotometry. To quantitate the relative abundance of D / L-Lactate in primary cell culture media, bacterial culture and tumor cytobrush samples, extracts were prepared and analyzed by Thermo Scientific TSQ Quantiva triple quadruple mass spectrometer coupled with a Dionex UltiMate 3000 HPLC system. Samples were stored in 80 C freezer and thawed on ice before analysis. 100 mL of samples were aliquoted and metabolites were extracted using cold 80 / 20 (v / v) methanol / water. Samples were then vortexed, centrifuged at 17,000 g for 10 min at 4 C, and organic layers were transferred to clean tubes, followed by evaporation to dryness underPATENT Attorney Docket No. MDA1370-1WO nitrogen. Dried extracts were reconstituted in 100 mL of 85 / 15 (v / v) acetonitrile / 50 mM ammonium acetate in water, and 5 mL was injected for analysis by liquid chromatography (LC)-MS. The mobile phase A(MPA) is acetonitrile and mobile phase B(MPB) is 33.3 mM ammonium acetate in water. Separation of D / L-Lactate was achieved on an Astec Chirobiotic R, 5um 2.1 3 150 mm column with 15% MPB isocratic condition. The flow rate was 400 mL / min at column temperate was 30 C. The total run time was 10 min. The mass spectrometer was operated in the MRM negative ion electrospray mode with the transitions: m / z 89.1 -> 43.0 for D-Lactate, m / z 89.1 -> 43.1 for L-Lactate, m / z 92.0 -> 45.1 for D-Lactate- 13 C3 m / z 92.0 -> 45.0 for L-Lactate-13C3. Raw data files were imported to Thermo Trace Finder software for final analysis. The relative abundance of D / L-Lactate was normalized by their stable isotope labeled internal standards.Comparative genomic analysis of patient-derived isolates and assembled lactobacillus metagenomes

[0117] Two patient-derived L. iners strains were also completely sequenced (Ptl, Pt2; Table 3). Near-complete assemblies (99.6% and 90.5% completeness) were produced for these strains and then compared with sequenced strains from patients without cancer: L. iners KY (complete genome; healthy patient) and ATCC 55195 (draft genome, 98.7% completeness; bacterial vaginosis patient) (FIG. 6E). The comparison of two cancer-derived strains with ATCC 55195 confirmed the similarity of 2 patient-derived L. iners with each other and notable differences from ATCC 55195 (FIG. 6E). The two cancer-derived strains demonstrated more significant enrichment of functions involved in bacterial immunity and virulence as compared to non-cancer derived strains (FIG. 7A). Further the Pathway Tools softwarel03 was used to generate PGDBs (Pathway Genome Databases) of the cancer-derived and noncancer-derived L. iners strains, in addition to a near complete assembly of a strain derived from a third patient’s WMS data, referred as I012T4 (97% completeness).

[0118] Table 3: Unique ReactionsUnique Reactions in L.inersL.iners L.iners L.iners L.inersOrganism: Unique ATCCI012T4 KY ptl pt2Reactions 55195a-D-galactose 6-phosphateP-D-galactose 6- phosphate yPATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 551952 L-ascorbate + an oxidizedunknown electron carrier + 2H+ — ► 2monodehydroascorbateradical + a reduced unknowntwo electron carrier2 L-ascorbate + hydrogenperoxide —> L-ascorbate +dehydroascorbate + 2 H2O y2 L-ascorbate + hydrogenperoxide + 2 H+ —> 2monodehydroascorbateradical + 2 H2O2 monodehydroascorbateradical —> L-ascorbate +dehydroascorbate + 2 H+ yN-(5-phosphoribosyl)- anthranilate + diphosphate =anthranilate + 5-phospho-a- D-ribose 1 -diphosphateS-adenosyl-L-methionine +a 5-(aminomethyl)-2- thiouridine34 in tRNA —> S- adenosyl-L-homocysteine +a 5-[(methylamino)methyl]- 2-thiouridine34 in tRNA +H+PATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersLiners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195sn-glycerol 3 -phosphate +dioxygen —> hydrogenperoxide + glyceronephosphatesn-glycerol 3-phosphate[in]+ amenaquinone [membrane] —>glycerone phosphatefin] + amenaquinolfmembrane]a 2-thiouridine34 in tRNA +GTP + a 5,10- methylenetetrahydrofolate +glycine + an oxidizedunknown electron carrier +H2O -> a 5- carboxymethylaminomethyl- 2-thiouridine34 in tRNA +GDP + a 7,8-dihydrofolate +a reduced unknown twoelectron carrier + phosphate+ 2 H+a 5- carboxymethylaminomethyl- 2-thiouridine34 in tRNA +FAD + H2O + 2 H+ -> a 5- (aminomethyl)-2- thiouridine34 in tRNA +glyoxylate + FADH2PATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195a 5-methylaminomethyl-2- (Se- phospho)selenouridine34 intRNA + H2O -> a 5- methylaminomethyl-2- selenouridine34 in tRNA +phosphatea branched-chain aminoacidfextracellular space] +H+[extracellular space] —> abranched-chain aminoacidfcytosol] + H+[cytosol]a dipeptidefextracellularspace] + atripeptidefextracellularspace] —> adipeptidefcytosol] + atripeptidefcytosol]a metal cationfextracellularspace] —> a metalcationfcytosol] ya metal cationfextracellularspace] + ATP + H2O —> ametal cationfcytosol] + ADP+ phosphate + H+a peptidefextracellularspace] + ATP + H2O —> apeptidefcytosol] + ADP +phosphate + H+PATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195apolysaccharidefextracellularspace] —> apolysaccharidefcytosol]a purinefextracellular space]—> a purinefcytosol] ya sugarfextracellular space]—> a sugarfcytosol] ya sugarfextracellular space]+ ATP + H2O -> asugarfcytosol] + ADP +phosphate + H+a [TusA sulfur-carrierprotein] - S -sulfany 1-L- cysteine + a [TusD]-L- cysteine —> a [TusA]-L- cysteine + a [TusD sulfur- carrier protein] -S -sulfany 1- L-cysteinea [TusD sulfur-carrierprotein] - S -sulfany 1-L- cysteine + a [TusE sulfurcarrier protein] -L-cysteine—> a [TusD] -L-cysteine + a[TusE sulfur carrier protein]- S-sulfanylcysteinean amino acid[extracellularspace] + ATP + H2O —> anamino acid[cytosol] + ADP+ phosphate + H+PATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195an amino acidfextracellularspace] + H+ [extracellularspace] —> an aminoacidfcytosol] + H+[cytosol]an oligopeptidefextracellularspace] + ATP + H2O —> anoligopeptidefcytosol] + ADP+ phosphate + H+an [HPr protein] -NTI- phospho-L-histidine + a-D- galactopyranosefout] —> a- D-galactose 6-phosphate[in]+ an [HPr]-L-histidinean [HPr protein] -NTI- phospho-L-histidine + [J-D- galactopyranose[out] —> [1- D-galactose 6-phosphate[in]+ an [HPr]-L-histidinean [HPr protein] -NTI- phospho-L-histidine +aldehydo-D-galactose [out]—> aldehydo-D-galactose 6- phosphate[in] + an [HPr]-L- histidinean [HPr protein] -NTI- phospho-L-histidine + D- fructofuranose[out] —> D- fructo furanose 1- phosphate[in] + an [HPr]-L- histidinePATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195an [HPr protein] -NTI- phospho-L-histidine + D- fructopyranosefout] —> D- fructopyranose 1- phosphatefin] + an [HPr]-L- histidinean [HPr protein] -NTI- phospho-L-histidine + D- fructosefextracellular space]—> D-fructose 1- phosphatefcytosol] + an[HPr] -L-histidinean [HPr protein] -NTI- phospho-L-histidine + D- galactopyranose[out] —> D- galactopyranose 6- phosphate[in] + an [HPr]-L- histidinean [HPr protein] -NTI- phospho-L-histidine + D- galactose[out] a D- galactose 6-phosphate[in] +an [HPr]-L-histidinean [HPr protein] -NTI- phospho-L-histidine + D- glucose[extracellular space]—> D-glucose 6- phosphate[cytosol] + an[HPr] -L-histidinePATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195an [L-cysteine desulfurase]- S-sulfanyl-L-cysteine + a[TusA]-L-cysteine —> an [L- cysteine desulfurase]-L- cysteine + a [TusA sulfur- carrier protein] -S-sulfanyl- L-cysteineATP + sn-glycerol 3- phosphatefextracellularspace] + H2O —> ADP + sn- glycerol 3- phosphatefcytosol] +phosphate + H+ATP + L- methioninefextracellularspace] + H2O —> ADP + L- methioninefcytosol] +phosphate + H+ATP + Mn2+ [extracellularspace] + H2O —> ADP +Mn2+[cytosol] + phosphate+ H+ATP +phosphatefextracellularspace] + H2O —> ADP +phosphatefcytosol] +phosphatefcytosol] + H+chloridefextracellular space]—> chloridefcytosol]PATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195cholinefextracellular space]+ ATP + H2O ->cholinefcytosol] + ADP +phosphate + H+Co2+ [extracellular space] +ATP + H2O ->Co2+[cytosol] + ADP +phosphate + H+cytosinefextracellular space]—> cytosinefcytosol] yD-xylose[extracellularspace] —> D-xylose[cytosol] ydehydroascorbate (bicyclicform) —> 2,3-didehydro-L- gulonate + H+ ydehydroascorbate + H2O —>2,3-didehydro-L-gulonate ydehydroascorbate + H2O +H+ —> dehydroascorbate(bicyclic form) ygeranyl diphosphate + a 5- [(methylamino)methyl]-2- thiouridine34 in tRNA —> a5-methylaminomethyl-2-(S- geranyl)thiouridine34 intRNA + diphosphatePATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195glutamatefextracellularspace] + 4- aminobutanoatefcytosol] —>glutamatefcytosol] + 4- aminobutanoatefextracellularspace]glycerol + ATP —> sn- glycerol 3 -phosphate + ADP+ H+ y glycerolfextracellular space]+ HTfextracellular space] —>glycerolfcytosol] +H+[cytosol]glycerolfout] —> glycerolfin] yglycine betainefextracellularspace] + ATP + H2O —>glycine betainefcytosol] +ADP + phosphate + H+L-ascorbate[extracellularspace] + H+ [extracellularspace] —> L- ascorbatefcytosol] +H+[cytosol]L-carnitine[extracellularspace] + ATP + H2O —> L- carnitinefcytosol] + ADP +phosphate + H+Mg2+[extracellular space]—> Mg2+[cytosol] yPATENTAttorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.iners Organism: Unique ATCCI012T4 KY ptl pt2 Reactions 55195Na+[extracellular space] +ATP + H2O —> Na+[cytosol]+ ADP + phosphate + H+ yphosphatefcytosol] <—phosphatefextracellularspace] yselenophosphate + a 5- methylaminomethyl-2-(S- geranyl)thiouridine34 intRNA -> a 5- methylaminomethyl-2-(Se- phospho)selenouridine34 intRNA + (2E)-3,7- dimethylocta-2,6-diene- 1 - thiolUnd-PP-{p-D-GlcNAc- ( 1 — >4)-Mur2 Ac-L- Ala-y-D- iGln- [N6-(Gly5 )] -L-Lys-D- Ala-D-Ala}(n+1) + apeptidoglycan internalsegment (S. aureus) —> apeptidoglycan with D, Dcross-link (S. aureus) + D- alanineuracilfcytosol] <—uracilfextracellular space] yuracilfextracellular space] +H+[extracellular space]uracilfcytosol] +H+[cytosol]PATENT Attorney Docket No. MDA1370-1WO Unique Reactions in L.inersL.iners L.iners L.iners L.inersOrganism: Unique ATCCI012T4 KY ptl pt2Reactions 55195xanthinefextracellular space]+ uracilfextracellular space]—> xanthinefcytosol] +uracilfcytosol]Zn2+ [extracellular space] +ATP + H2O ->Zn2+[cytosol] + ADP +phosphate + H+Total 6 51 3 4 1Postprocessing of 16S ribosomal RNA sequencing

[0119] The 16S rRNA gene data analysis incorporated phylogenetic-based and alignmentbased approaches to maximize data resolution. Sequence read pairs were demultiplexed using unique molecular barcodes, and reads were merged using USEARCH version 7.0.1090. 16S analysis was performed using custom analytic packages and pipelines developed at the Alkek Center for Metagenomics and Microbiome Research at Baylor University to create summary statistics and quality control measurements for each sequencing run, as well as multi-run reports and data-merging capabilities for validating built-in controls and characterizing microbial communities across large numbers of samples or sample groups. 16S rRNA sequence reads were processed and analyzed using the QIIME2 microbiome bioinformatics platform (version 2020.11).

[0120] Rarefaction sampling depth was not utilized and thus the data was not rarefied for the analysis presented in this study. Raw FASTQ paired-end sequences were imported and demultiplexed as QIIME2 artifacts. Amplicon Sequence Variant (ASV) feature tables were constructed using DADA2 denoising.

[0121] Phylogenetic reference tree construction was performed using a pre-trained Naive Bayes classifier and the q2-feature-classifier plugin. For rectal samples, the taxonomic classifier used was trained on the SILVA 138 515F / 806R region of sequences. For cervical tumor samples a custom classifier trained on a cervicovaginal specific database was used. Phyla-level eukaryotic, organellar, and unclassified taxa were inspected for removal prior to diversity and compositional analysis for quality control purposes, but rare or low abundant features were not targeted for removal or filtering. Alpha diversity and evenness metrics were calculated through QIIME2. ThePATENT Attorney Docket No. MDA1370-1WO indices used in this study are Shannon Diversity Index (SDI), Simpson Diversity, Faith’s Phylogenetic Diversity (PD), Fisher’s index, Pielou’s evenness, Simpson’s evenness, and Observed ASV’s (Observed Features).Postprocessing of tumor SMS

[0122] Postprocessing of SMS data was implemented using a set of software tools summarized in the key resources table. The paired-end raw sequence reads in fastq format were filtered and trimmed using BBMap. To remove contamination by human DNA, which was abundant in the cervical swabs, the Bowtie 280 was used to align filtered and trimmed sequencing reads to an hg38 reference genome (GCA 000001405.28). After removing the contaminated human reads, the remaining reads were assembled into contigs by both MEGAHIT [doi.org / 10.1093 / bioinformatics / btv033] and metaSPAdes. Only contigs that were larger than 1000 bp were used for binning by MetaBAT2.86 Genes were predicted in each assembled contigs by Prodigal87 and then annotated by KofamKOALA, which assign KOs ID, gene name, function, and EC number. Taxonomic classification of each contig was implemented by CAT and BAT. All the software tools were run with default parameters. Versions and sources of the software tools or packages used in the pipeline are listed in the key resources table. Output of the assembly was a set of assembled contigs foreach sample, their taxonomic annotation, predicted genes, their location in the contig, strand, size, KO IDs, genes names, gene functions (description), and EC numbers. Some genes were annotated by 2 or more KOs or / and EC numbers.Postprocessing of RNA sequencing data

[0123] Processing of RNA-seq reads was implemented by the Genomic Medicine computational pipeline at MDACC. The processed reads were mapped to the hgl9 reference by RNA-seq aligner STAR110 and then quantified as counts by HTSeqlll,112 and annotated by ANNOVAR. Normalization of the gene counts and identification of differentially expressed genes (DEGs) were implemented by R library ‘edgeR’ and Timma’ with ‘voom’ as describedl 13 using R version 4.2.2 (2022-10-31). Differentially active pathways were determined by Quantitative Set Analysis of Gene Expression (QuSAGE) as describedl 14 with default parameters. Hallmark pathways gene set was downloaded from MSigDb v.7.5.1.115Postprocessing of Lactobacillus isolates shotgun metagenome sequences

[0124] Postprocessing of the obtained fastq files was implemented by the same computational workflow used for postprocessing of SMS data. The workflow, which is described above, generated assembled contigs for each strain that were further curated to avoid duplications. The assembled contigs for each strain were annotated using a prokaryotic genome annotation pipeline DFAST.PATENT Attorney Docket No. MDA1370-1WO

[0125] The software implements gene predictions for protein coding sequences, rRNA, tRNA, and CRISPR, and infers protein functions. Completeness check was calculated by DFAST at the genus level (Lactobacillus, 14 genome, 238 marker sets) and revealed completeness values 98.7% for ATCC 55195 strain and 99.6% and 90.5% for Ptl and Pt2 respectively. The level of contamination calculated by DFAST was 0.6-0.67%. Identity check evaluated taxonomy identity by calculating average nucleotide identity and by comparison the value with 13000 reference genomes using FastANI software,

[0126] HMM scan against TIGRFAM and RPSBLAST against COG were enabled as advanced options of the annotation. Gene predictions were done using Prodigal87 as an option provided by DFAST. Characteristics of the assemblies are provided in Table 3. The PathoLogic componentl 18 of the Pathway Tools software 25.5 and MetaCyc v.25.5119 were used to generate PGDBs for draft genomes of 2 L iners strains (ptl and pt2) isolated from cervical swabs of 2 CC patients, ATCC 55195 strain isolated form a patient with bacterial vaginosis, I012T4 strain (draft genome assembled from WMS data of CC patient 12) and for the complete genome of L. iners isolated from a healthy individual. The default parameters were used if not specified to run the tools. The Pathway tools were also used to predict transcription units, generate contigs overviews, pathway diagrams, and to compare the generated PGDBs. Characteristics of the generated PGDBs are provided in Table 3.Detection and postprocessing of reads of bacterial origin in TCGA datasets

[0127] Primary tumor samples from all publicly available datasets on cBioPortal for NSCLC, HNSCC, COAD and SKIN were included. Single and paired-end reads were quality trimmed and quality filtered using BBduk. Reads of human origin were filtered using the bloom filter from the BB tools suitel08,120 using a cutoff of >15 31mers matching the human genome (GRChg38). Paired-end sequencing reads were merged using BBMerge from the BB tools suite 1 under “maxstrict” parameters. Combined merged and single-end reads were dereplicated using VSEARCH. Dereplicated reads were normalized using normalized-by-median.py from the khmer suite.

[0128] The resulting readset was mapped against all bacterial reference entries in GenBank (gbbct) using BLASTnl24 with an e-value cutoff of 0.00001, a word length of 29, and a 95% identity cutoff. In parallel, DIAMOND88 was used to perform a translated alignment of the normalized reads against all bacterial proteins in gbbct. All aligned reads (nucleotide and translated alignments) were extracted and aligned to GenBank primate (gbpri), vertebrate (gbvrt), and SILVA125 16S database vl38. Reads with alignment bit scores higher for non-bacterial entries were eliminated. Candidate references genomes were selected from the combinedPATENT Attorney Docket No. MDA1370-1WO nucleotide and translated nucleotide alignments using the minimum set cluster function (clusterReferences.pl) from VirMAP.

[0129] Selected references were used as scaffolds to reconstruct putative genomes. Genomes counts were calculated by remapping the original set of reads (post quality trimming and filtering) to the reference genomes selected in the prior step. Taxonomies with a significant skew between total input kmers and kmer diversity were filtered as suspected contaminants.Lactobacillus iners-specific real-time quantitative PCR assay

[0130] The Lactobacillus zhers-specific real-time quantitative PCR assay was internally developed to validate the detection and quantification of Lactobacillus iners (L. iners) in clinical patient specimens. It was first established a standard benchmark for testing using ten- fold serial dilutions of genomic DNA derived from Lactobacillus iners strain AB 107 ATCC BAA-3226DQ™ ranging from 5 nanograms to 5 x 10'7nanograms that were used as positive-controls for all future experiments. This standard was tested alongside nuclease-free water control, as well as a negative-control using genomic DNA derived from a Bacteroides intestinalis isolate to determine any cross-contamination or off-target amplification. The limits of detection and quantification of L. iners using the standard showed a minimum of 30 genome copies, with no amplification in the no-template nor off-target controls. It was also co-validated the assay against a commercially available, Thermo Fisher Scientific, ID: Ba04646257_sl L. iners qPCR assay that also showed a limit of detection around 30 genome copies, with a limit of quantification at a minimum of around 3,000 genome copies. The internally developed qPCR as well as the commercially available qPCR with 40 cervical swab DNA samples obtained from cervical cancer patients was tested, which were shown to have a mix of Lactobacillus species using both 16S rRNA gene-specific sequencing and whole genome sequencing. The internally developed targeted qPCR detected the presence of L. iners in 8 out of 40 samples, whereas the commercially developed L. iners qPCR detected L. iners in 13 out of 40 samples. It was observed a higher instance of false detection of L. iners using the commercially developed assay, whereas the internally developed assay showed consistently higher specificity to L. iners detection and quantification across sample replicates that were validated in multiple repeated experiments. Lastly, it was aimed to assess any amplification in species closely related to L. iners in both qPCR assays by testing 8 known clinical Lactobacillus isolates that were previously speciated using the mass spectrometry-based Bruker MALDI-TOF Biotyper that showed high similarity and potential detection of L. iners on the platform. Two additional known L. iners clinical isolates were included during testing as comparison alongside the standard benchmark, where no detection was found using either qPCR assay with any other Lactobacillus species. Overall, an L. zhers-specific qPCRPATENT Attorney Docket No. MDA1370-1WO that consistently detected and quantified the genomic load of L. iners in multiple clinical specimens was designed and tested, that was co-validated using a commercially available qPCR.

[0131] An L. / ' / zers-spcci tie real time qPCR assay for detection and quantification of L. iners was designed and validated (Tables 4 and 5, FIG. 15, FIGs.l6A-16B, FIGs. 17A-17B).

[0132] Table 4: Thermo Fisher qPCR Shows Potentially Higher Sensitivity to L. iners; PRIME-TR qPCR Shows Potentially Higher SpecificitySample ID L. iners Log(10) Copy L. iners Log(10) Copy Number (PRIME-TR) Number (Thermo Fisher)1089-C1-T2-E1 2.11028 1.935059 1026-C2-T1 3.912376 4.0630231032-C2-T1 0 1.050789 1068-C2-T1 0 0.79375 I038-C2-TI T618011 3.555475 I086-C2-TI 3.801229 4.038369 I097-C2-TI 0 0 / 744468 1105-C2-T1 0 1.777878 A1124-C2-T1 3.71954 3.6983 A1127-C2-T1 4.189848 4.415331 B1245-C1-T2-E1 0.733362 0.590805 B1309-C1-T2-E1 0 2.232674 B1337-C1-T2-E1 3.287168 3.388584

[0133] Table 5: No Detection of Non-zners Lactobacilli and Other Bacteria Displays Higher Sensitivity for L. inersPatient Isolate PRIME-TR ThermoFisherPatient 366 Lactobacillus + +inersPatient 370 Lactobacillus + +inersLactobacillus crispatus - -PATENT Attorney Docket No. MDA1370-1WOPatient Isolate PRIME-TR ThermoFisherLactobacillus gasseri - - Lactobacillus jensenii - - Lactobacillus johnsonii - - Lactobacillus fermentum - - Lactobacillus rhamnosus - - Lactobacillus marinus - - Gardnerella vaginalis - - Bacteroides intestinalis - -Statistical analysis

[0134] All code and standardized datasets used for the analysis are publicly available in the supplementary material (Datas SI and S2). All raw and processed 16S and SGS sequences, including assembled isolate bacterial genomes are uploaded to SRA and dbGap. All analyses presented were performed on the initial cohort, the validation cohort, and the full cohort independently. Strict evaluation for batch effects was performed, including sensitivity analyses for endpoints of interest by batch for each timepoint, institution, and patient demographics. Batches were analyzed separately by institution, with no differences in the outcomes. It was also noted that batch 4 had a higher number of features than the other batches (FIGs. 12A-12H).Therefore, sensitivity analyses was performed with and without it to ensure that it did not affect the results. Linear discriminant analysis effect size (LEfSe) was used to identify taxa that were enriched in baseline samples, with the clinical response set as “class”.

[0135] A linear discriminant analysis (LDA) score of 4.0 was used with an 0.05 alpha value for the Kruskal- Wallis all-against-all test. To validate LEfSe, MaAsLin2128 was performed with default parameters and the same input as LEfSe. Kaplan-Meier (KM) curves were generated and Cox proportional hazards (Cox PH) modeling were performed for the association of species with an LDA score R4 for RFS and OS in the pilot cohort. It was evaluated the associations between the different tumor alpha diversity, evenness, and richness metrics at baseline with response to CRT and survival in the pilot cohort using Wilcoxon Rank-sum tests and a univariate Cox PH model, respectively. Baseline tumor samples were classified into community state types (CST)PATENT Attorney Docket No. MDA1370-1WO based on the composition of the vaginal microbial community using VALENCIA38 and visualized the tumor microbiome using a stacked taxonomy bar plot. Univariate Cox PH models were built for RFS and OS. The models included the tumor and gut baseline alpha diversity metrics, as well as the relative counts of L. iners and species identified on LEfSc with an LDA score R4, along with relevant clinical and demographic characteristics. Covariates that were significant at the univariate level (p < 0.05) were fitted using a multivariate Cox PH model. It was tested for associations between gut alpha diversity, evenness, and richness, as well as clinical and demographic characteristics, and baseline L. iners status using a Chi-square or Fisher’s exact test for categorical variables and an independent t-test for continuous variables. It was quantified changes in tumor alpha diversity metrics and relative counts of L. iners over time using Bonferroni false discovery rate (FDR)-adjusted paired t-tests. Unsupervised hierarchical clustering of the top 25 species in the baseline samples was conducted using the mclust machine learning algorithm in the full cohort.

[0136] It was then performed survival analysis on the cluster groups using Cox PH modeling for RFS and OS with G. vaginalis, P. bivia, and A. vaginae. It was also analyzed changes in these three species over time using a paired t-test. For viral annotation, virMAP was used as previously described. The resulting sequencing reads were trimmed and filtered using the BBtools suite. Reads with at least 50 bp and an entropy value of at least 0.7 were retained. The resulting reads were checked for kmer (k = 31) collisions against all Papillomaviridae (GenBank taxa ID = 151340) using a bloom filter. Reads with no collisions to Papillomaviridae were filtered if a kmer collision against the human genome was detected using a similar methodology. The remaining reads, including the subset that collided with HPV genomes, were used as input for VirMAP. VirMAP was run using default settings. Raw VirMAP viral abundances represent the number of reads assigned to each viral taxa ID. Although these abundances can be interpreted as being proportional to other viral IDs or input reads, they are not normalized against any host-derived metric. Therefore, VirMAP HPV read coverage was normalized against single-copy human gene coverage. First, single-copy gene coverage values were calculated on a per-sample basis. Singlecopy genes were identified by aligning all human coding sequences (CDS) to the human genome (hg38) using BLAST. Genes were considered single-copy genes if the alignment span of the CDS was >10,000 base pairs; all CDS were uniquely aligned (genes with overlapping alignment ranges were removed); and the CDS alignment was >99%. In total, 17,737 genes satisfied these constraints.

[0137] To calculate coverage per gene, any read that overlapped with the full alignment length per CDS (both exonic and intronic) were included. Mean CDS region coverage was calculated byPATENT Attorney Docket No. MDA1370-1WO dividing the total length of aligned reads by the length of the aligned region per CDS. Overall coverage per sample was calculated by taking the mean of all CDS coverage values. HPV coverage values were obtained by dividing the sum of all aligned HPV read lengths by the average complete genome length of the corresponding HPV subtypes. Finally, HPV normalization values were calculated by dividing the HPV coverage values by the per-sample mean gene coverage, thus approximating HPV copies per human genome copy. Total Fungal reads were annotated from NCBI and log transformed to reduce variability and skewness and normalized to the total library size resulting in log normalized fungal reads per million (RPM).

[0138] LEfSe was used to identify baseline gut bacteria associated with CRT response. E. shigella was found to be associated with response (LDA R4) and so KM survival curves were generated with log rank tests for comparison and performed Cox PH modeling for RFS and OS. LEfSc was also used to identify bacteria enriched in the baseline gut microbiome of patients with L. iners+ tumors. It was correlated baseline gut and tumor L. iners relative counts using the Kendall’s G coefficient. An independent Wilcoxon test was used to compare T cell repertoire characteristics between L. iners+ and L. mers-tumors at baseline. The T cell repertoire metrics used were the maximum frequency, maximum productive frequency, out-of-frame rearrangements, out-of-frame templates, productive clonality, productive entropy, productive rearrangements, productive templates, sample entropy, total rearrangements, and total templates. Additionally, it was tested for differences in the presence of specific motifs and clone groups previously identified among L. iners+ and L. mers-tumors at baseline using chi-square tests. Clarivate Metacore pathway, network and process enrichment analyses and GSEA Hallmark pathway analysis were used to identify pathways, processes and networks enriched in treatment groups with default parameters. For metabolomics, no normalization was performed. NGCHM software was used for heatmap clustering analysis. Normalized data was median transformed before generating NGCHM. NGCHM plots are interactive and can be used to search a specific compound, zoom-in and to highlight the value of a specific data point. PCA-plus plots were generated using Batcheffect package. ANOVA was used to find the differentially expressed compounds in two different biological covariates. Differential analysis was performed in several steps using following contrasts. One-Way ANOVA was performed separately for all three time points to identify compounds significantly differing between treatment groups at that specific time point, two-way ANOVA was performed to estimate the effects of treatment group and / or time on each compound. Interaction P-value indicates the combined P-value of above mentioned both covariates. Tukey’s test was used for post-hoc analysis of pairwise comparison.PATENT Attorney Docket No. MDA1370-1WO

[0139] For survival analysis of TCGA data, WGS and RNASeq BacMap feature tables for each cancer type were queried for presence of any of the 93 LAB species in 3 or more samples. It was then generated KM survival analyses for dichotomized presence of each bacteria for RFS and OS. The species that were found to be significantly associated with poor survival (p < 0.05) and generated KM curves for RFS and OS were pooled. All high quality were used, reference genomes in the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) to classify the bacteria as obligate L-lactate producers, obligate D-lactate producers, or both. Statistical significance was set at an a of 5% for a two-sided p value. All available samples were used for analyses. Analyses were conducted using RStudio 2023.03.0 + 386 Cherry Blossom.EXAMPLE 2Tumor Lactobacillus iners are associated with non-response to CRT and decreased recurrence-free survival

[0140] To identify initial bacteria of interest in the tumor microbiome (tumor-resident bacteria), it was first performed linear discriminant analysis (LDA) effect size (LEfSe) in a pilot cohort of 43 patients using 16S ribosomal RNA sequencing data (16S) for associations with chemoradiation response. Lactobacillus iners was significantly associated with non-response to CRT (N = 10), while Proteobacteria (phylum), Gammaproteobacteria (class), and Actinobacteriota (phylum) were associated with response to CRT (FIG. 2C; N = 31; CDA score >4) in the pilot cohort. Next, the relationship of these organisms with recurrence-free survival (RFS) was evaluated. Increased relative counts of tumor-resident L. iners were significantly associated with decreased RFS (RFS; Cox proportional hazard ratio [Cox HR] 5.29 [95% CI 2.44-8.14]; log rank p = 0.0003), while Proteobacteria (phylum), Gammaproteobacteria (class), and Actinobacteriota (Phylum) were not associated with RFS in the pilot cohort (FIG. 3A- 3C; all p > 0.05). Cervical tumor microbial diversity (Simpson, Faith’s phylogenetic diversity, and Fisher), evenness (Pielou), or richness (total observed features) were not associated with response or RFS (FIG. 3D- 3M), using both rarefied and non-rarefied data and MaAsLin2 (FDR q value = 0.07, p value = 0.0007). To validate the association of L. iners with RFS, an additional 58 patients across both institutions were enrolled. The presence of any tumor-resident L. iners at baseline remained significantly associated with CRT non-response. In all patients, tumoral L. iners was present in 46% of samples (FIG. 2D) and the presence of L. iners remained associated with decreased RFS (log rank p = 0.035; FIG. 2E).

[0141] In univariate analysis of all patients with baseline samples (N = 96), increased relative counts of L. iners at baseline were also significantly associated with lower RFS (Table 6; Cox HRPATENT Attorney Docket No. MDA1370-1WO 3.7 [95% CI 1.0-13.3; p = 0.04) and lower overall survival ([OS], Table 6; Cox HR 10.4 [95% CI 1.8-60.3]; p = 0.009). Proteobacteria, Gammaproteobacteria, and Actinobacteriota remained unasso-ciated with RFS or OS, as did tumor microbiome evenness, diversity, and richness (Table 6). Other clinical and demographic variables associated with shorter RFS on univariate analysis included higher International Federation of Gynecology and Obstetrics (FIGO) 2009 stage (III -IV vs. I-II; p = 0.01) and lower gut microbiome diversity (p = 0.049).

[0142] Table 6: Univariate (UV) and multivariate (MV) Cox proportional hazard models for recurrence-free and overall survival for all patients with baseline samples (N = 96).PATENTAttorney Docket No. MDA1370-1WO Recurrence-free Survival3Overall Survival UV MV UV MV1p HR p P HR P Variable value (95%CI)bvalue value (95%CI) value Tumor L. Inersc<0.01d5.79 <0.01 0.02 8.60 <0.01(1.98- (1.77- 16.95) 71.77) InstitutionLBJeMDACCf0.29 0.07Age (years) 0.36 0.41RaceAsian / Black / Hispanic 0.16 0.99White 0.52 0.20BMIg(kg / m2) 0.84 0.40Smoking statusNeverFormer 0.76 0.29Current 0.43 0.63HistologyNon-squamoushSquamous 0.68 0.12LVSI'NoYes 0.91 0.86Unknown 0.57 0.79FIGO 2009 stagei0.01 2.49 0.02 0.27 2.82 0.07(1.18- (0.93- GradeOther / Unknown1 0.99 0.992 0.09 0.223 0.83 0.70HPV typeHPV 16 / 18Negative / Other 0.19 0.07Cisplatin cycles 0.36 0.81Radiation dose 0.92 0.03Antibiotic usekNoYes 0.58 0.08Nodal statusNegativePositive 0.84 0.99PATENT Attorney Docket No. MDA1370-1WORecurrence-free Survival Overall SurvivalUV MV UV MV1p HR p P HR PVariable value (95%CI)bvalue value (95%CI) valueTumor 0.51 0.44dimension (cm)Gut diversity1<0.05 0.03 0.30 0.01(5.6E-05 - Gut evenness1" 0.18 0.03

[0143] Relative counts of L.iners and overall tumor microbiome diversity (Simpson, Faith, and Fisher), evenness (Pielou), or overall richness (Observed features) did not change significantly during or after CRT (FIG. 2F and FIG.4A-4E).EXAMPLE 3L. iners abundance is an independent predictor of poor recurrence-free and overall survival on multivariate analysis

[0144] On multivariate (MV) Cox proportional hazard (PH) analysis for RFS in all patients, adjusting for stage and gut microbiome diversity, only higher L. iners abundance remained associated with decreased RFS (Table 6; Cox HR 5.79 [1.98-16.95]; p = 0.001), as did higher FIGO stage (2.49 [1.18-5.25]; Cox PH p = 0.016). Gut microbiome diversity was no longer significant (Cox PH p = 0.30). Sensitivity analyses for model stability with only gut diversity and L. iners abundance confirmed L. iners was significant for RFS, while gut diversity was not. There was no difference in RFS based on relative counts of L. iners for patients with small tumors (FIGO 2009 stage I-II; N = 52) versus large tumors (Fig-ure 1H, FIGO 2009 stage III-IV; N = 47). Even in these patients, the presence of tumoral L. iners (N = 26) still predicted significantly shorter RFS (FIG. 21; 26; log rank p = 0.022).

[0145] High L. iners abundance was also significantly associated with worse OS on MV analysis (Table 6; Cox HR 12.7 [2.4-66.5]; p = 0.006) when adjusted for stage (p = 0.07). Independent models for L. iners adjusted for gut microbiome diversity and evenness were constructed independently due to small OS event numbers, and L. iners remained significant in both models (FIG.2G, gut Simpson diversity. L. iners Cox HR 5.9 [95% CI 1.2-29.7]; p < 0.0031;FIG. 5A, gut Pielou evenness L. iners Cox HR 6.5 [95% CI 1.3-32.9]; p = 0.024).PATENT Attorney Docket No. MDA1370-1WO EXAMPLE 4L. iners is not a surrogate for another gut or tumor microbe, microbial signature, or clinical feature

[0146] No clinical, demographic, or gut microbiome metrics were associated with tumoral L. iners (Table 7). L. iners+ tumors had slightly lower overall tumor microbiome alpha diversity; however, diversity was not associated with RFS or OS. No other tumor or gut compositional metrics, besides gut Simpson diversity and Pielou evenness, were significantly associated with L. iners, RFS, or OS (Table 8), including gut and tumor Faith’s phylogenetic diversity Fisher’s alpha, observed features, Shannon diversity, or Simpson evenness (all p > 0.05).

[0147] Table 7: Pathologic and clinical variables associated with the presence of tumoral L. iners (N = 96).Tumor L. iners Status Variable L. iners- (N = 52) L. iners+ (N = 44) p-valucaN (%) Mean N (%) Mean Institution i LBJ Hospital1’ 15 (29) i 6 (14) i i 0.07MDACO 37 (71) 38 (86) | | Age (years) | i 47.1 (9) | | 43.0 (11) i 0.06i Race i Black / Asian / Other 6 (12) 6 (14) 0.21 Hispanic 27 (52) 15 (34) | White | 19 (37) | i 23 (52) ij BM I'1(kg / m2) _ _ j 30.2 (6) | _ | 28.9 (7) j 0.34 _ | Smoking Status| Never | 32 (62) | i 26 (59) i | 0.61 Former _ 14 (27) _ 15 (34) _ _6112) 3 (?) Histology Non-squamouse10 (19) 11 (25) 0.5042 (81) 33 (75) i 1. VS 11| i No ( 12 (23) i i 9 (21) i i 0.80 | Yes | 3 (6) | 4 (9) i Unknown | 37 (71) i 31 (70) i FIGO 2009 stage** _ _ _ _ _ | 26 (50) 26 (59) r~037 | i726 (50) 1 18 (41) i iPATENT Attorney Docket No. MDA1370-1WO Grade Indeterminate / 7 (14) 11 (25) 0.08Unknown in6*,2> H2>! 2 | 25 (48)! | 15 (34) | 3 _ 14 (27). | 17 (39) | _ _ II PV genotype! HPV 16 / 18 | 35 (71)! | 24 (56) |! 6.11 Negative / Other 14 (29) 19 (44) Cisplatin cycles 36 (69) 5.0 (1) 23 (54) 5.0 (1) 0.92Antibiotic use1' j No _ 36 (69) j 23 (54) _ j 6,12 _ | Yes 16 (31) 20 (47) | | Nodal status Negative / 20 (38) | 17 (39) j | 0.98 Unknown | Positive j 32 (62) |! 27 (61)!! Tumor! 5.5 (2) 5.1 (2)! 0.38 | Faith’s PI)' (Gut) _ | 12.1 (3)" _ 12,7 (3) | 0.30 _ | Fishers 20.5 (9) 23.0 (8) 0.17 Observed 150.8 166.4 (58) 0.22! Pielou’s! 0.7 (0) 0.7 (6)! 6.23 Shannon 5.0 ( 1 ) 5.2 ( 1 ) 0.15 Simpson’s 6.1 (0) 0.1 (0) 0.53 Simpson 0.9 (0) 6.9 (6) 0.36

[0148] Table 8: Univariate Cox proportional hazard survival analysis for other baseline tumor and gut microbiome metrics in all patients with baseline samples available (N=96), related to FIGs 2A-2I and FIG. 8A-8P.Recurrence-F reeOverall Survival SurvivalType HR (95°A)C1) pval HR (95%C1) pval Faith’s POaTumo 0.97 (0.77-1.22) 0.80 0.97 (0.70-0.36) 0.88 Fisher’s Alpha Tumo 1.00 (0.92-1.09) 0.99 1.00 (1.00-1.00) 1 Observed Features Tumo 1.00 (0.98-1.01) 0.73 1.00 (0.98-1.02) 0.90PATENT Attorney Docket No. MDA1370-1WO Pielou’s Evenness Tumo 0.80 (0.13-4.96) 0.81 0.77 (0.06-10.54) 0.85 Shannon Diversity Tumo 0.98 (0.76-1.28) 0.91 0.99 (0.68-1.46) 0.98 Simpson’s Evenness Tumo 0.69 (0.04-13.46) 0.81 1.88 (0.04-85.00) 0.75 Simpson Diversity Tumo 1.00 (0.22-4.50) 1.00 1.03 (0.12-9.11) 0.98 Faith’s PD Gut 1.01 (0.89-1.15) 0.88 0.89 (0.72-1.09) 0.26 Fisher’s Alpha Gut 1.00 (0.96-1.04) 0.95 0.98 (0.91-1.05) 0.57 Observed Features Gut 1.00 (0.99-1.01) 0.72 1.00 (0.98-1.01) 0.47 Pielou’s Evenness Gut 0.04 (0.0004-4.21) 0.18 0.001 (1.83E-06 - 0.03c Shannon Diversity Gut 0.80 (0.52-1.24) 0.32 0.57 (0.29-1.10) 0.09 Simpson’s Evenness Gut 0.02 (2.81 E-06 - 0.40 2.3E-07 (7.5E-14 - 0.04 Simpson Diversity Gut 0.003 (1.01E-05 -0.99) 0.049 6.5E-05 (2.87E-08 - 0.01 Prevotella Tumo 1.04 (0.11-9.89) 0.97 1.43 (0.06-36.54) 0.83 Porphyromonas Tumo 1.06 (0.04-29.93) 0.97 0.33 (0.001-95.83) 0.70 Gammaproteobacte Tumo 2.24E-05 (5.4E-12- 0.17 0.80 (0.001-949.69) 0.95 Actinobacteria Tumo 0.03 (0.00-1.82) 0.09 1.47 (0.05-39.84) 0.82 Proteobacteria Tumo 0.003 (1.6E-06 -6.94) 0.14 0.15 (0.0001-196.16) 0.61 Gardnerella Tumo 0.19 (0.01-5.68) 0.34 1.42 (0.05-40.17) 0.84 Prevotella bivia Tumo 0.76 (0.04-16.09) 0.86 0.01 (5.87E-07 - 0.32 Atopobium vaginae Tumo 0.01 (1.65E-08 - 0.49 308.96 (0.002- 0.35 Escherichia shigella Gut 23.06 (0.12-4272.69) 0.24 10.24 (0.01- 0.52

[0149] Unsupervised clustering revealed two L. iners+ clusters, co-occurring with either Gardnerella vaginalis or Atopobium vaginae, and an L. iners- cluster with Prevotella bivia; cluster membership did not change significantly during CRT and was not independently associated with outcomes (FIG. 4F-4N; Table 7, all p > 0.05).

[0150] There was also no association of overall viral, human papillo-mavirus (HPV)-specific viral load or fungal load with presence of L. iners (FIG.4N-4P). Antibiotic use was not associated with £. iners (Table 2) or outcomes (Table 1).

[0151] Presence and abundance of L. iners in the gut was significantly associated with initial CRT response on LEfSe, in addition to Es-cherichia / Shigella) (FIG. 5B), but not with RFS or OS (FIG. 5C-5D; all Cox PH and KM p > 0.05). Patients with gut L. iners also had tumor L. iners'. the only bacterial species in the gut enriched (LDA score R4) in patients with L. iners+ tumors was L. iners with no direct correlation between abundances (FIG. 5E-5G).PATENT Attorney Docket No. MDA1370-1WO EXAMPLE 5L. iners does not affect baseline or dynamic overall or antigen-specific T cell repertoire

[0152] In other cancers, bacteria prime immune response to standard cancer therapy and immunotherapy. To explore whether there were differences in T cell repertoire or clonal expansion in response to cancer therapy, it was performed tumoral T cell repertoire at serial time points27 (N = 199). L. iners - tumors had overall higher counts of TCR templates (8,175 vs. 14,600 t test p = 0.03; FIG. 6A), CD4+ T cells, and CD8+ T cells (FIGs. 6B-6C) at baseline, suggesting higher T cell infiltration. Both L. iners+ and L. iners - tumors had a decrease during CRT in productive clonality and overall templates (FIGs. 6D-6I); L. iners - tumors rebounded slightly earlier at the end of treatment and by week 12, no differences were identified in serial clonal TCR repertoire or motifs (FIGs. 6J-6T), or in clonal expansion of HPV-specific TCRs (FIG.6U). T cell recognition and expansion did not appear to be the primary mechanism for poor survival.EXAMPLE 6L. iners induces chemoradiation resistance in cervical cancer cell lines

[0153] To test whether L. iners from cervical cancers could directly cause radiation resistance independent of an immune effect, it was cultured, isolated, and characterized L. iners strains from cervical tumors, then filtered bacterial supernatant for cell-free supernatant (CFS). To identify the optimal supplement ratio of CFS in the cell culture medium and the culture condition, it was performed serial dilution assays using a HPV16+ cervical squamous cell carcinoma (CSCC) cell line, CaSki (FIG. 7A). It was generated a cervical cancer patient-derived organoid line (PDO, Bl 188) which develops a dense 3D morphology, exhibits immunofluorescence profiles consistent with CSCC (FIGs.8A-8B), and is sensitive to both ionizing radiation (IR) and cisplatin treatments (FIGs. 7B-7C). A line of genomically stable primary cells was generated after several passages (Bl 188 primary cells).

[0154] Bl 188 PDOs were incubated for two weeks with 20% CFS harvested from two cancer-derived L. iners strains (CC-Z. iners), one commercial non-cancer-associated L. iners strains (NC-L. iners), or control (CTRL, 20% NYC Broth), prior to treat-ment with IR, cisplatin (CIS), gemcitabine (GEM), or 5 -fluorouracil (5FU), or their combination. PDOs cultured with CC-Z. iners CFS displayed more aggressive growth and resistance than CTRL, with higher organoid count, larger orga-noid size (FIGs. 8A-8B, FIGs. 7D-7E), and increased cell viability after IR (FIG. 8E). CC-Z. iners andNC-Z. iners CFS also caused increased cell viability in Bl 188 primary cells (FIG. 8F). HeLa, SiHa, and CaSki cells all exhibited significantly increased cell viability withZ. iners treatment at all doses of irradiation (FIGs. 8G-8I). CC-Z. mers-trcatcd Bl 188 cellsPATENT Attorney Docket No. MDA1370-1WO were resistant to GEM (FIG. 8J), but not CIS (FIG. 8K) or 5FU (FIG. 8L) alone. With the addition of IR, they exhibited resistance to GEM-IR, CIS-IR, and 5FU-IR (FIGs. 8M-8O). L. iners similarly induced GEM resistance in CaSki cells (FIGs. 7F-7H), but to no chemo therapeutics without IR in SiHa or HeLa cells (FIGs. 7I-7M). It was also evaluated cell viability after IR in HeLa cells using cancer-derived and non-cancer derived L. crispatus. L. crispatus did not induce treatment resistance (FIG. 7N). No radiation sensitization was observed with UV-killed, PBS-washed L. iners (FIG. 8P) suggesting the factors mediating radiation resistance were secreted by L. iners rather than an effect of bacterial cell wall components.EXAMPLE 7L. iners alter gene expression in lactate signaling pathways

[0155] Next, to explore how L. iners CFS could alter cancer cell sensitivity to IR, it was performed RNA sequencing of pre treated Bl 188 cells. This proposed mechanism for the effect of L. iners on cancer cell metabolism is given in FIG.9A. It was found that cells treated with L. iners CFS versus NYC broth control had significantly altered gene expression (FIG. 9B). Metacore pathway analysis revealed enrichment in several pathways closely linked to lactate signaling and lactate dehydrogenase (LDH) activity, including reactive oxygen species (ROS)-induced cellular signaling and hypoxia- inducible factor 1 (HIF - 1 ) transcription targets, F GFR signal transduction, Her2 / ERBB2 signaling, 31-33 and p53 / p73 -dependent apoptosis (FIG.9C); Gene Set Enrichment Analysis (GSEA) Hallmark Pathway analysis confirmed enrichment in oxidative stress / ROS-induced cellular signaling and HIF- la transcription targets, along with the GSEA pathway for skeletal muscle genes, which is also highly regulated by lactate (FIG. 10A).EXAMPLE 8L. iners are obligate L-lactate producers and CC-Z. iners+ tumors are L-lactate enriched

[0156] All lactobacilli produce lactate as the final product of fermentation via LDH activity after carbohydrate utilization. One of the distinguishing characteristics of L. iners, compared to beneficial lactobacilli, is that its smaller genome uniformly does not contain the D-LDH gene, rendering it an obligate L-lactate producer. L-lactate is also the predominant enantiomer (97%-99%) in mammalian cells and tumors. Although cancer cells can produce D-lactate by the methylglyoxal pathway, this likely negligibly affects metabolism.

[0157] CC-Z. iners produced only L-lactate in vitro (FIG. 9D), while cancer-derived and noncancer derived L. crispatus produced primarily D-lactate (FIG. 9E); all cancer-derived Z. iners genomes did not contain D-LDH. It was validated this using quantitative L and D-lactate ion chromatography-mass spectrometry assays. CC and NC-Z. iners had significantly higher L-lactatePATENT Attorney Docket No. MDA1370-1WO levels than broth controls (FIG. 9F). In cervical tumor samples, it was confirmed that L-lactate levels were > 1,000-fold greater than D-lactate (FIG. 9G).

[0158] Non-targeted metabolic profiling of CFS from NC and CC-L. iners and L. crispatus strains revealed distinct metabolic network alterations in glycolysis, the pentose phosphate pathway, and the regulation of redox balance for CC-L. iners, all of which are linked to oncogenic lactate metabolism (FIG. 9H and FIG. 91).EXAMPLE 9L-lactate recapitulates treatment resistance in cervical cancer cell lines

[0159] To determine whether L-lactate alone could induce chemo-therapy and IR resistance similar to L. iners CFS, cervical cancer cell lines were pretreated with four isoforms of lactate: L-lactate, D-lactate, sodium L-lactate, and sodium D-lactate for two weeks prior to chemotherapy or IR treatment. The lactate concentrations and pH were maintained until harvest. L-lactate, but not other isoforms, in the culture medium consistently recapitulated the treatment resistance of cervical cancer cells to IR and GEM in all cell lines, with varying effects observed for CIS and 5FU (FIGs. 9J-9K and FIGs. 10B-10E), which was consistent with the effect of L. iners CFS.EXAMPLE 10L. iners increases tumor metabolic activity in response to radiation-induced stress

[0160] Although at baseline, there was no difference in measured L-lactate levels between L. iners + and L. iners - tumors; interestingly, L-lactate levels (but not D-lactate levels) in L. iners+ tumors increased steeply from baseline to the end of CRT, nearly doubling by week 5 (FIG. 9L-9M). Irradiated L. iners - treated Bl 188 cells also significantly increased L-lactate production versus broth (CTRL) or L. iners alone, and demonstrated remarkable upregulation in glycolysis, TCA cycle, redox balance and nucleotide, and short-chain fatty acid assembly, particularly after irradiation (FIGs. 9N-9O).

[0161] These data demonstrate that L. iners can potentiate lactate utilization, production, and metabolic activity in response to metabolic stress, including from IR.EXAMPLE 11L. iners+ tumors have upregulated glycolysis compared to L. iners - tumors

[0162] L. iners is a facultative anaerobe, and can make ATP via aerobic respiration or switch to fermentation under anaerobic conditions, efficiently producing lactate. Thus, it was hypothesized that the lactate production and metabolic rewiring might be magnified in the hypoxic tumor microenvironment in patients. Principal component analysis of non-targeted metabolomics confirmed distinct metabolite profiles fori, iners + (N = 30) andZ. iners- tumors (N = 36; FIG.11 A; DSC p < 0.005), and significant enrichment of unique metabolites inZ. iners+ tumors (FIG.PATENT Attorney Docket No. MDA1370-1WO 11B), overall indicative of higher metabolic activity. Supervised clus-tering confirmed clusters of metabolites differentially enriched in L. iners+ vs. L. iners - tumors (FIG. 11C). Metabolites significantly enriched in L. iners+ tumors were pyruvate, indicative of increased glycolysis, ATP and NADH, both indicative of upregulated TCA cycling and downstream electron transport chain activity, and deoxyguanosine triphosphate and deoxyuridine monophosphate, both precursors for increased DNA synthesis, which can be driven by excess ATP. Galactaric acid was also significantly enriched in L. iners + tumors; galactaric acid is an indicator of increased fermentation and lactate production in lactobacilli. The metabolic pathways most upregulated in L. iners+ tumors were the Warburg effect, glycolysis, glutamate metabolism, and galactose metabolism (FIG. 11D and FIGs. 10F-10H).

[0163] The most significantly enriched metabolite in L. iners - tumors was 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR). AICAR is an analog of AMP and activates the AMP-kinase cascade in response to ATP deprivation, such as in downregulated glycolysis. AICAR is pro-apoptotic in this setting and strongly suppresses cancer cell proliferation in response to ATP deprivation. It is used as a cancer therapy sensitizer in various cancers and can reverse Warburg metabolism. These findings strongly suggest that L. iners plays a significant role in contributing to energy production and DNA synthesis within the tumor microenvironment.EXAMPLE 12Cancer-derived L. iners acquires additional genes for lactose utilization during carcinogenesis

[0164] L. iners is a common organism in a healthy cervicovaginal micro-biome and regularly undergoes horizontal gene transfer to evade antibiotics and adapt to changing nutrient, pH, and oxygenation conditions. It was hypothesized that CC-L. iners in patients with cervical cancer acquired additional genes during carcinogenesis, which may contribute to the metabolic effects observed. To identify potential functions unique to CC-L. iners, the complete genomes of two CC-L. iners isolates and two NC-Z. iners isolates were sequenced. It was also performed SMS on base-line tumor samples (N = 44) and assembled Lactobacillus genomes. It was compared these to complete genomes of L. iners KY, isolated from a healthy individual. All contigs annotated by L. iners in the metagenomes were combined and contigs that were annotated by any Lactobacillus (99% L. iners) to represent a cervical cancer Lactobacillus “pangenome” (FIG.12A). 593 genes (81%) were shared between CC-L. iners andNC-Z. iners. 120 (16%) genes were unique to CC-L. iners, while NC-Z. iners contained only 18 unique genes (2%; FIG. 13A). There were also more shared KOs (N = 100; 14%) between dysplasia-associated Z. iners (N = 14) and CC-Z. iners than between NC-Z. iners and CC-Z. iners (FIG. 13B). Overall, this higher geneticPATENT Attorney Docket No. MDA1370-1WO commonality between dysplasia-associated L. iners and CC-L. iners suggests that these genes were ac-quired prior to or during carcinogenesis, rather than after cancer development. I was also performed gene, function, and pathway analysis (KO, KEGG, and BRITE) to determine the function of genes acquired by CC-L. iners that were not present in NC-Z. iners. It was compared the genomes of CC-L. iners isolates and a near-complete assembly of L. iners obtained from a patient sample with NC-Z. iners. A complete comparison of genes, functions, and pathways unique to and shared by CC-Z. iners and NC-Z. iners (FIGs. 12B-12C) demonstrated that, while all Z. iners strains had the lacA, lacD, and lacR genes involved in conversion of galactose to D-glyceraldehyde-3-P and fructose-6-P, only CC-Z. iners also contained the additional lacG gene, which encodes 6-phospho-beta-galactosidase, which converts lactose to galactose-6-P and glucose (FIG. 13C, FIG. 12C, and FIG. 12D). Lactobacilli can easily convert lactose to lactate, and galactose to lactate in the reverse direction, via the Leloir pathway and the tagatose-6-phosphate pathway. All Z. iners+ patient samples and Z. iners isolates contained only L-LDH, while none contained the gene for D-LDH. Non-targeted metabolomics of CC-Z. iners and NC-Z. iners isolates revealed that the only upregulated pathway in CC-Z. iners vs. NC-Z. iners was galac-tose metabolism, consistent with the genomic findings (FIG. 13D).EXAMPLE 13DNA damage and response in cervical cancer cells after CFS treatment

[0165] It was also investigated intrinsic DNA sensitivity and repair in CC-Z. iners and NC-Z. iners-treated cells. While gene expression with anyZ. iners versus control involved lactate signaling pathways (FIGs. 9A-9N and FIG. 12E), there were also notable differences in gene expression specifically for unirradiated CC-Z. / / zers-trcatcd cells versus NC-Z. / / zers-trcatcd cells (FIG. 13E-13F, FIG. 12F, and FIG. 12G), with significant downregulation of several DNA damage response pathways, DNA replication and initiation, G2 / M and intra-S phase checkpoints, and E2F transcription targets. It was also noted a general, slightly higher resistance to IR for CC-Z. iners vs. NC-Z. / hers-trcatcd cells (FIG.9A-9O). After irradiation, CC-Z. iners versus NC-Z. / / zers-trcatcd cells demonstrated significant gene expression alterations, with upregulation of epithelial-mesenchymal transition, NFKb signaling, and KRAS signaling, and downregulation of hypoxia response signaling (FIG. 12H). The gene expression data for treatment with Z. iners demonstrated increased expression of oxidative stress / ROS-induced cellular signaling and HIF-1 transcriptional targets in the cells cultured with L. iners CFS compared to cells cultured with broth both before (FIG. 9C and FIG. 12C) and after irradiation (FIG. 12D), suggestive of increased ROS and hypoxia in the microenvironment. ROS elevation correlates with increased g-H2AX and causes induction of double-strand breaks and assurance of DNA damage response activation. It was evaluated g-H2AX foci kinetics at different time points (2 h to 24 h) after 8PATENT Attorney Docket No. MDA1370-1WO Gy irradiation. All cells expressed the strongest foci intensity 2 h after IR, with decreasing intensity over time, indicating DNA damage repair. CC-L. iners exhibited less initial foci generation as compared to NC-Z. iners, while both exhibited more initial foci formation versus CTRL (FIG. 13G and FIG.13H). CC-L. iners exhibited the most rapid return to normal levels, indicating efficient repair overall.

[0166] It was also noted altered expression in S phase and G2 / M checkpoint regulation genes (FIGs. 11E-11F), and a trend toward increased incorporation of EdU by cells treated with L. iners (FIG. 131) suggestive of a dysfunctional intra-S phase checkpoint, and slight distinctions in redox reaction metabolism for CC-L. iners vs. NC-Z. iners (FIG. 9H and FIG. 90). Lactose degradation via the lacG gene in CC-Z. iners produces glucose as a byproduct (FIG. 13D), which can also induce G2 / M checkpoint arrest by the Cdkl / CyclinB complex and enhance tumor survival post irradiation despite DNA damage, consistent with the gene expression data. Further investigation is needed.EXAMPLE 14Z. iners and similar lactic acid bacteria are relevant in other cancer types

[0167] It was also analyzed microbiome composition of tumor samples from anal (N = 70), vaginal, and vulvar cancer (N = 44) at MDACC and reprocessed raw reads from whole-genome sequencing and RNA sequencing in The Cancer Genome Atlas for head and neck squamous cell carcinoma (HNSCC; N = 171), colorectal adenocarcinoma (COAD; N = 502), non-small-cell lung cancer (NSCLC; N = 1047), and melanoma (SKIN; N = 106). Z. iners was identified in anal, vaginal, vulvar, colorectal, and lung cancers but, not unexpectedly, extremely rarely, since Z. iners is a commensal vaginal microbe. Still, Z. iners in NSCLC (N = 57; 5.4%) was strongly associated with decreased RFS (FIG. 14A; 21 months vs. Not reached [NR]; log rank p = 0.0077).

[0168] Although Z. iners is almost exclusively a cervicovaginal microbe, lactic acid bacteria (LAB) are ubiquitous across body sites. It was hypothesized that functionally similar LAB could impact tumors in their respective niches. 92 bacterial species whose genomes (N = 1,586) contained the lacA, lacG, lacD, and lacR genes found in CC-Z. iners were identified; 46 in more than 3 patients (FIG. 14B-14D).40% of these species (17 / 46) were associated with decreased RFS and / or OS in other cancers (FIG. 14D).

[0169] The presence of any tumoral lacGDRA bacteria was significantly associated with lower RFS in all four cancers, including NSCLC (FIG. 14E; 27 months vs. 59 months; p <0.0001), COAD (FIG. 14F; 50 months vs. 84 months; log rank p = 0.0025), HNSCC (Figure 6G; 20 months vs. NR; p = 0.0017), and SKIN (Table 8; 6 months vs. NR; log rank p = 0.0041). Significant species included Entero-coccus faecalis (COAD), E. faecium (COAD), L. paracasei (HNSCC), L. johnsonii (HNSCC, NSCLC), L. paragasseri (HNSCC), Staphylococcus capitis (NSCLC), S. hominisPATENT Attorney Docket No. MDA1370-1WO (COAD, NSCLC), S. lugdunensis (SKIN), S. saccharolyticus (NSCLC), S. wameri (COAD), S. anginosus (COAD), and Streptococcus mitis (COAD) (Table 8).EXAMPLE 15Obligate L- or D-lactate production by genetically similar LAB is associated with survival

[0170] 30% (5 / 16) of the obligate L-lactate producers (with L-LDH gene but no D-LDH) were associated with poor patient survival (L. iners, S. infantis, S. intermedins, S. oralis, and Streptococcus sp. oral taxon 064), while none of the five obligate D-lactate producers (Leptotrichia sp. oral taxons 221 and 498, Leptotrichia trevisanii, Leptotrichia wadeii, S. ilei) were (FIG. 14D);40% (2 / 5) of the D-lactate producers (L. trevisanii and L. wadeii) were associated with increased rather than decreased RFS and / or OS, consistent with previous reports that D-lactate-producing LAB in the gut microbiome are protective. No other obligate L-lactate or mixed L- / D-lactate producers were associated with decreased RFS.

[0171] In HNSCC, there was nearly 100% RFS (FIG. 14H; Median NR vs. 13 months; p < 0.0001) and OS (FIG. 141; Median NR vs. 15 months; p < 0.0001) in patients with only obligate D-lactate producers versus a median of 13 months in patients with at least one detrimental L-lactate-producing LAB, suggesting that D-lactate could outcompete L-lactate for monocarboxylate transporters (MCTs) in tumor cells. While L. iners is a commensal cervicovaginal microbe, its functions are likely relevant in other cancers.DISCUSSION

[0172] Here, it was demonstrate that cervical cancer-associated L. iners, an obligate L-lactate-producing facultative anaerobic bacterium, induces treatment resistance through efficient L-lactate production and metabolic rewiring in tumors. This is supported by strong clinical associations, the induction of chemotherapy and radiation resistance by L. iners or L-lactate, and its high lactate production in vitro and in tumors after irradiation. This finding is not limited to cervical tumor bacteria or cervical tumors; instead, it was argued that tumor-associated LAB participate in lactate-mediated metabolic rewiring in a similar fashion to described tumor-stroma or tumor-immune cell interactions, with broad implications in many cancer types.

[0173] Lactate is a powerful exchangeable metabolic coupling molecule between cancer cells, rather than simply a metabolic waste product, and cross-talks with many known treatment resistance mechanisms. Metabolic coupling occurs via exploitation of the reversible LDH enzyme to convert lactate to pyruvate or vice versa, and in turn, recycling NAD to NADH+. Tumor lactate and LDH expression are correlated with aggressive tumor biology and poor survival across cancer types, including cervical cancer, perhaps because a higher lactate level in tumors is representative of higher glucose-to-lactate metabolic flux. It can serve as a metabolic fuel, a “hormone”sensed byPATENT Attorney Docket No. MDA1370-1WO membrane receptors, and an epigenetic modifier through histone lac-tylation, all of which can directly affect DNA synthesis and lead to radiation and chemotherapy resistance.

[0174] Lactate is a “lactormone, ’’acting in a hormonal positive feedback loop and serving as an exchangeable molecule and a key regulator of interactions between tumor cells and surrounding cells, including tumor-stroma, cancer cell-cancer cell, cancer cell-astrocyte, and cancer cellfibroblast interactions. Cancer-associated fibroblasts can be activated by SIRTUIN3 release as a result of tumor-stroma contact, which in turn causes mitochondrial oxidation and upregulates MCT4 expression, lactate biosynthesis, glucose transporter 1, and glycolysis. SIRTUIN3 is a key molecule in cervical cancer. Lactate is also a strong promoter of dendritic cells and tumor-associated macrophage recruitment in the tumor microenvironment. It was proposed that L. iners in the tumor microenvironment has a symbiotic relationship with cancer cells to fuel growth via these pathways, similar to what has been demonstrated for fibroblasts or immune cells.

[0175] Lung cancers, which share many key metabolic genes with cervical cancers, including PI3K / AKT, STK11, and TP53, exhibit a striking preference for lactate utilization over glucose to fuel the citric acid cycle. This activity is particularly profound when cancer cells adapt to oxidative stress, wherein excess lactate leads to up-regulation of MCT1 and MCT4 for overall lactate influx and efflux. This phenomenon of “lactate addiction”results in efficient use of lactate to fuel the TCA cycle and other metabolic pathways, and an even higher preference for lactate over glucose. L. iners in the tumor microenvironment may similarly “prime”cervical cancer cells and magnify the lactate feedback loop that results from oxidative stress after radiation or chemotherapy.

[0176] Many therapeutic opportunities exist to target LAB involved in therapeutic resistance. Modification of the vaginal microbiome is feasible, inexpensive, and relatively low risk. For example, in bacterial vaginosis, the application of topical metronidazole followed by reconstitution of a beneficial strain of L. crispatus, known as LACTIN-V, resulted in vaginal colonization by L. crispatus in nearly 80% of patients. Other potential therapies to eliminate L. iners, such as topical application of bacteriocins, lytic phages, bioengineered bacteria, or clinically proven probiotics could be repurposed for cancer therapy. Lactobacilli themselves are promising candidates for bioengineered microbial cancer therapeutics, due to the simplicity of genome editing and general lack of pathogenicity. L.iners itself could be exploited to deliver anticancer drugs with tumor specificity, given its strong com-mensality to cervical tumors and the cervicovaginal niche.

[0177] Outside of bacterial targeting, systemic use of targeted therapies related to lactate uptake and conversion could also be useful in patients with tumoral LAB. Several clinically available LDH inhibitors exist, which could prevent conversion of lactate to pyruvate in these tumors. There is known strong synergy between gemcita-bine and LDH inhibitors, so this data demonstrating extreme treat-PATENT Attorney Docket No. MDA1370-1WO ment resistance with L-lactate provide rationale for adjuvant or oncurrent use of an LDH inhibitor in these patients. Further, there are several promising MCT inhibitors in various stages of clinical and pre-clinical development, including first in class single inhibitors of MCT1 and MCT2, and MCT1 / MCT4 and MCT2 / MCT4 dual inhibitors. MCT1 inhibitors with tumor specificity and a very high affinity for MCT1 or LDH inhibitors could be used as a targeted therapy in patients with lactate-producing bacteria.

[0178] Overall, these data provide strong evidence of an opportunity for targeted interventions in the tumor microenvironment of lactic-acid bacteria-populated tumors for future clinical translation.

[0179] Although the invention has been described with reference to the examples, it will be understood that modifications and variations are encompassed within the spirit and scope of the invention. Accordingly, the invention is limited only by the following claims.

Claims

PATENT Attorney Docket No. MDA1370-1WO What Is Claimed Is:

1. A method of predicting resistance to chemotherapy and / or radiation therapy in a subject in need thereof comprising:detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria is indicative of resistance to chemotherapy and / or radiation therapy, thereby predicting resistance to chemotherapy and / or radiation therapy in the subject.

2. The method of claim 1, wherein the lactic acid bacteria is an L-lactate-producing lactic acid bacteria.

3. The method of claim 2, wherein the L-lactate-producing lactic acid bacteria is Lactobacillus iners (L. iners).

4. The method of claim 1, wherein detecting the presence of lactic acid bacteria comprises performing a polymerase chain reaction (PCR) assay on a genomic region for the lactic acid bacteria, 16S rRNA sequencing, shotgun metagenomic sequencing (SMS), T cell receptor repertoire sequencing (TCR), in situ hybridization, digital spatial profiling, deep microbiome sequencing, immune profiling, targeted bacterial culture, DNA synthesis assay, ultra-high resolution mass spectrometry (HRMS), D- / L-Lactic Acid assay, or a combination thereof.

5. The method of claim 4, wherein detecting the presence of the lactic acid bacteria comprises detecting a unique genomic region of the lactic acid bacteria.

6. The method of claim 5, wherein detecting the unique genomic region for the lactic acid bacteria comprises performing a PCR assay.

7. The method of claim 6, wherein the PCR assay is selected from the group comprising quantitative PCR (qPCR), real-time PCR, rapid PCR, and multiplex PCR.

8. The method of claim 7, wherein the PCR assay is a qPCR.

9. The method of claim 8, wherein performing the qPCR assay comprises using primers and a probe targeting a unique genomic region of L. iners.

10. The method of claim 9, wherein the unique genomic region of L. iners is located between genome coordinates 509,916 and 513,468 in reference genome CP049230.1.

11. The method of claim 9, wherein the primers comprise a sequence having at least about seventeen (17) nucleotides of SEQ ID NO:1 or SEQ ID NO:2 and which bind to the unique genomic region of L. iners.PATENT Attorney Docket No. MDA1370-1WO 12. The method of claim 11, wherein the primers comprise SEQ ID NO: 1 (GCACCAACTAATGCTAATATCATTT) and SEQ ID NO: 2 (TATTGACGAATAACAAGCAAGAATC).

13. The method of claim 9, wherein the primers comprise a sequence having about fifty (50) or fewer nucleotides of SEQ ID NO: 1 or SEQ ID NO:2 and which bind to the unique genomic region of L. iners.

14. The method of claim 9, wherein the probe comprises SEQ ID NO: 3 (TGCTCTTTAACGGGTATCGAATGTGCCCAG).

15. The method of claim 9, wherein the probe comprises a sequence having at least about seventeen (17) nucleotides of SEQ ID NO:3 and which binds to the unique genomic region ofZ. iners.

16. The method of claim 9, wherein the probe comprises a sequence having about fifty (50) or fewer nucleotides of SEQ ID NO:3 and which binds to the unique genomic region of L. iners.

17. A method of treating cancer in a subject comprising:a) detecting presence of lactic acid bacteria in a sample from the subject, wherein the presence of lactic acid bacteria in the sample is indicative of a need for treatment; andb) optionally administering to the subject a therapeutic agent targeting the lactic acid bacteria, a metabolic product of the lactic acid bacteria and / or a cancer treatment; thereby treating cancer in the subject.

18. The method of claim 17, wherein the lactic acid bacteria is L-lactate-producing lactic acid bacteria.

19. The method of claim 18, wherein the L-lactate-producing lactic acid bacteria is L. iners.

20. The method of claim 17, wherein detecting the presence of lactic acid bacteria comprises performing a polymerase chain reaction (PCR) assay on a genomic region for the lactic acid bacteria, 16S rRNA sequencing, shotgun metagenomic sequencing (SMS), T cell receptor repertoire sequencing (TCR), in situ hybridization, digital spatial profiling, deep microbiome sequencing, immune profiling, targeted bacterial culture platform, DNA synthesis assay, ultra-high resolution mass spectrometry (HRMS), D- / L-Lactic Acid assay, or a combination thereof.

21. The method of claim 17, wherein detecting the presence of the lactic acid bacteria comprises detecting a unique genomic region of the lactic acid bacteria.

22. The method of claim 20, wherein detecting the unique genomic region for the lactic acid bacteria comprises performing a PCR assay.PATENT Attorney Docket No. MDA1370-1WO 23. The method of claim 22, wherein the PCR assay is selected from the group comprising quantitative PCR (qPCR), real-time PCR, rapid PCR, and multiplex PCR.

24. The method of claim 23, wherein the PCR assay is a qPCR.

25. The method of claim 24, wherein performing the qPCR assay comprises using primers and a probe targeting unique genomic region of L. iners.

26. The method of claim 21, wherein the unique genomic region of L. iners is located between genome coordinates 509,916 and 513,468 in reference genome CP049230.1.

27. The method of claim 25, wherein the primers comprise a sequence having at least about seventeen (17) nucleotides of SEQ ID NO:1 or SEQ ID NO:2 and which bind to the unique genomic region of L. iners.

28. The method of claim 27, wherein the primers comprise SEQ ID NO: 1 (GCACCAACTAATGCTAATATCATTT) and SEQ ID NO: 2 (TATTGACGAATAACAAGCAAGAATC).

29. The method of claim 25, wherein the primers comprise a sequence having about fifty (50) or fewer nucleotides of SEQ ID NO: 1 or SEQ ID NO:2 and which bind to the unique genomic region of L. iners.

30. The method of claim 25, wherein the probe comprises SEQ ID NO: 3 (TGCTCTTTAACGGGTATCGAATGTGCCCAG).

31. The method of claim 25, wherein the probe comprises a sequence having at least about seventeen (17) nucleotides of SEQ ID NO:3 and which binds to the unique genomic region ofZ. iners.

32. The method of claim 25, wherein the probe comprises a sequence having about fifty (50) or fewer nucleotides of SEQ ID NO:3 and which binds to the unique genomic region of L. iners.

33. The method of claim 17, wherein the cancer is selected from cervical cancer, vaginal cancer, colorectal cancer, lung cancer, head and neck cancer, or skin cancer.

34. The method of claim 33, wherein the cancer is cervical cancer.

35. The method of any of claims 1-34, wherein the therapy or cancer treatment is chemotherapy, radiation therapy, immunotherapy, resection surgery, hormone therapy, stem cell or bone marrow transplant, or a combination thereof.

36. The method of any of claims 1-35, wherein the therapeutic agent targeting the lactic acid bacteria is an antimicrobial therapy, a metabolic inhibitor, or a combination thereof.

37. The method of claim 36, wherein the antimicrobial therapy comprises metronidazole, bacteriocins, lytic phages, bioengineered bacteria, probiotics, bioengineered microbial therapeutics, bacterial consortia, live biotherapeutics, or a combination thereof.PATENT Attorney Docket No. MDA1370-1WO 38. The method of claim 36, wherein the metabolic inhibitor is a lactate dehydrogenase (LDH) inhibitor, a monocarboxylate transporters (MCT) inhibitor, or a combination thereof.

39. The method of any of claims 1-38, wherein the sample is tissue biopsy, plasma, saliva, tumor sample, blood sample, and / or vaginal sample.

40. The method of claim 39, wherein the sample is vaginal sample.

41. A kit comprising:a) primers, wherein the primers comprise a nucleic acid sequence set forth in SEQ ID NO:1 and SEQ ID NO:2,b) a nucleic acid probe set forth in SEQ ID NO:3; andc) instructions for using the primers and probe for lactic acid bacteria specific PCR on a biological sample.

42. The kit of claim 41, further comprising a sample collection device for obtaining the biological sample from a subject.

43. The kit of claim 41, wherein presence of lactic acid bacteria in the sample after PCR is indicative of resistance to chemotherapy and / or radiation therapy.

44. The kit of any of claims 41-43, wherein the sample is tissue biopsy, plasma, saliva, tumor sample, blood sample, and / or vaginal sample.

45. The kit of claim 44, wherein the sample is vaginal sample.

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