Phenocopying alzheimer's disease in aging t-cells to improve Anti-tumor immunity

Abstract

The present invention relates to inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in aging T-cells to improve anti-tumor immunity and attenuate tumor growth.

Description

[0001] PHENOCOPYING ALZHEIMER’S DISEASE IN AGING T-CELLS TO IMPROVE ANTI TUMOR IMMUNITY

[0002] FIELD OF THE INVENTION

[0003] The invention relates generally to Alzheimer’s disease associated amyloid precursor protein and beta-amyloid peptide-40 improving anti-tumor immunity in aging T-cells.

[0004] All publications, patents, patent applications, and other references cited in this application are incorporated herein by reference in their entirety for all purposes and to the same extent as if each individual publication, patent, patent application or other reference was specifically and individually indicated to be incorporated by reference in its entirety for all purposes. Citation of a reference herein shall not be construed as an admission that such is prior art to the present invention.

[0005] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0006] This invention was partially made with Government support under National Institutes of Health CA214461, DE016572, and P01 CA203628. The Government has certain rights in the invention.

[0007] BACKGROUND OF THE INVENTION

[0008] The inverse association between Alzheimer’s disease (AD) and cancer incidence has been established in several epidemiological studies1'8, with some studies reporting up to a 50% decrease in cancer development in patients with AD7. Although several biological mechanisms common to both diseases have been proposed to contribute to this association2, the primary mechanism that regulates this inverse association between AD and cancer remains unknown. It has been suggested that biological mechanisms and molecular pathways common to both diseases are at the root of this association, with hypotheses implicating the Warburg effect, the unfolded protein response, metabolic deregulation, as well as several molecular players such as p53, Wnt, and PIN12. However, the possible contribution of the adaptive immune system in AD patients to reducing cancer incidence has not been studied despite the critical involvement of immune system alterations in both diseases5’9'19.

[0009] Aging is a common risk factor for developing AD and cancer20’21, and the changes in the adaptive immune system, namely T-cells, with aging have been studied previously. Memory T-cell function substantially decreases with aging22'26, with alterations in mitochondrial function and mitochondrial dynamics in T-cells as one of the hallmarks of these aging-induced changes22’26'28. Memory T-cells depend on mitochondrial and lipid metabolism for function and survival29, and the bioactive sphingolipid ceramide has recently been implicated in modulating mitochondrial metabolism and suppressing anti-tumor responses in aging T-cells26. Produced by ceramide synthases 1-6 (CerS 1-6), ceramide is the central molecule in sphingolipid metabolism, which plays both structural and functional roles in cell biology and cell death signaling30. Six different ceramide synthases have been characterized (CerSl-6)31, each with a high specificity towards the length of the fatty acyl chain in the ceramide molecules it synthesizes32. The localization of ceramide synthases to the mitochondria and the synthesis of ceramide in the outer mitochondrial membrane recruit the autophagic machinery and induce mitophagy26’33'35by binding autophagosome-associated LC3. Recent evidence suggests that in response to aging stress, CerS6 localizes to the mitochondria of aging T-cells, producing C14- and C16-ceramides, which in turn induce ceramide-dependent hyperactivated mitophagy, restricting mitochondrial function and inhibiting the T-cell anti -turn or immunity26.

[0010] While the increase in ceramide-dependent hyperactivated lethal mitophagy in aging T-cells is detrimental to their anti-tumor function26, homeostatic mild mitophagy in aging neurons is essential for healthy aging due to involvement in mitochondrial quality control. Multiple neurodegenerative diseases have been characterized by dysfunctional mitophagic processes in neurons36, as described in Parkinson’s disease (PD)37'39, Huntington’s disease4041, amyotrophic lateral sclerosis (ALS)42'44, chronic traumatic encephalopathy (CTE)35, and Alzheimer’s disease (AD)45'52. Previous studies demonstrated the accumulation of amyloid-beta precursor protein (APP) and its product amyloid P (Ap40 and Ap42) and C-terminal fragments (APP-CTF) in the outer mitochondrial membrane through association with TOMM complex (including Tom20 / 40 proteins), which inhibits mitophagy47’51’53’54. To this end, mitochondrial fission-fusion dynamics through alterations of Drpl, Parkin, and Pinkl functions55’36, which play essential roles in mitophagy induction and mitochondrial quality control during healthy brain aging, have also been shown to be disrupted in various neurodegenerative diseases including CTE, Parkinson’s disease (PD), and AD34’35’57

[0011] APP is known to be expressed and processed in T-cells at low levels58'60. Accumulation and processing of APP lead to mitophagic changes in neurons61’62. However, the roles of APP or its cleavage products AP40 and AP42 in the inhibition of aging-stress mediated and ceramidedependent hyperactivated mitophagy in T-cells, which could improve anti-tumor functions of aging AD T-cells, have not been investigated previously.

[0012] A need exists in the art to inhibit ceramide-dependent lethal mitophagy in aging T-cells to improve anti-tumor immunity and attenuate tumor growth.

[0013] SUMMARY OF THE INVENTION

[0014] The present invention is directed to a method of inhibiting aging-stress mediated and ceramidedependent hyperactivated mitophagy in T-cells, comprising the step of overexpressing Alzheimer’s disease-associated APP in the T-cells.

[0015] BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1. Alzheimer’s disease protects mice from endogenous and exogenous tumor growth. (A) Prevalence of cancer among AD cases and non- AD controls, 2016-2019 and 2021 Medical Expenditure Panel Survey (MEPS). Weighted prevalence accounts for the complex MEPS survey design and weights. The ‘n’ represents the actual number of MEPS survey participants with AD diagnosis (AD cases) and without an AD diagnosis (non-AD controls) aged >60 years. The population sizes represent an approximate estimate of the number of individuals with the stated diagnosis in the United States. (B) Tumor-free survival of young WT, old WT, and old 3xTg mice exposed to 4NQO carcinogen in their drinking water. None of the 3xTg mice developed oral tumors (drop in Kaplan-Meier curve explained by non-tumor related death). *p<0.05. (C, D) Confocal images of mouse tongue tumors from the 4NQO study showing increased LC3-Tom40 colocalization in tumors extracted from old WT mice compared to the 3xTg counterparts, indicating a higher level of mitophagy in the TILs in the WT tongue tumors. Scale bar is equal to 10pm. Quantification of colocalization in (D). Data are means ± SDs from 4 independent experiments (n=4). **p<0.01. (E) Percentage of Foxp3+ Tregs out of CD4+ CD8- T-cells as determined by multiplex imaging of tongue tumors taken from mice in (B). Data are means ± SDs from 4 independent experiments (n = 4). *p<0.05. (F) Tumor growth of subcutaneously implanted B16-F10 tumor cells in old WT or old 3xTg mice with or without CD3+ T-cell depletion. Data are means ± SEMs. **p<0.01. (G, H) Increased IFNy positivity in CD4+ (WT: n=7, 3xTg: n=5) and CD8+ (WT: n=4, 3xTg: n=3) TILs extracted from the B16-F10 tumors in the 3xTg mice compared to WT controls (G), and lower levels of FoxP3+ TILs (WT: n=5, 3xTg: n=3) (H). Data are means ± SDs from independent experiments. *p<0.05, ***p<0.001, ****p<0.0001. (I) Combination of immunofluorescence and PLA in B16-F10 tumors from old WT vs old 3xTg mice, highlighting CD3+ TILs in green and measuring the interaction between LC3-Tom40 by PLA in red. Quantification of PLA signals / CD3+ cell in the right panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3). ****p<0.0001. (J) Tumor growth of subcutaneously implanted B16-F10 tumor cells in old C57BL / 6 (B6) versus old APP-PS1 mice. Data are means ± SEMs from 3 independent experiments (n = 3) (Left panel). Western blot of APP levels in APP -PSI versus 3xTg T-cells. Actin used as a loading control (Right panel).

[0017] Figure 2. APP accumulates in the mitochondria of mouse Alzheimer’s T-cells and protects T-cell function in aging (A) Viability of old T-cells from WT vs 3xTg mice measured by flow cytometry of Ghost Dye™. Data are means ± SDs from 8 independent experiments (n = 8). (B, C) Intracellular Flow Cytometry results of IFNy and IL 10 in CD4+ (B) and IFNy in CD8+ (C) T- cells taken from young (2-3mo) WT, old (10-12mo) WT, and old (10-12mo) 3xTg mice. IFNy (Y: n=4, 0, 3xTg: n=7), IL10 (Y: n=4, 0, 3xTg: n=7). Data are means ± SDs from independent experiments. *p < 0.05, **p<0.01, ***p<0.001, ****p<0.0001. (D) Viability of M0C2 tumor cells in tumor-killing assay after co-culture with activated T-cells, comparing tumor-killing potential of old WT T-cells to old 3xTg T-cells. Control refers to the viability of the tumor cells in the absence of T-cells. Data are means ± SDs from 4 independent experiments (n = 4). **p<0.01, ***p<0.001, ****p<0.0001. (E) Western blot showing the levels of APP in old WT vs old 3xTg T-cells. Actin blot is used as a loading control (Left Panel). Quantification of WB results relative to actin (Right Panel). Data are means ± SDs from 4 independent experiments (n = 4). *p < 0.05. (F) Western blot of APP levels in mitochondrial vs. cytosolic fractions of T-cells from old WT vs. old 3xTg T-cells showing APP accumulation in mitochondria of T-cells. Mitochondrial COXIV and cytosolic actin are used as loading controls (Left panel). Quantification of APP in the mitochondria relative to COXIV (Right panel). Data are means ± SDs from independent experiments (WT: n=2, 3xTg: n = 5). *p < 0.05. (G) Confocal images of old WT vs. old 3xTg T-cells stained for APP in red and Tom20 in green (Upper panel), showing the increased colocalization of APP with Tom20 in the 3xTg T-cells (Bottom panel). Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5). ****p<0.0001. (H) Proximity Ligation Assay (PLA) showing the interaction between APP and Tom20 in old WT vs old 3xTg T-cells. Quantification of signals per cell shown in the bottom panel. Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5). ****p<0.0001.

[0018] Figure 3. ATAD3-mediated shuttle of CerS6 to mitochondria is inhibited in 3xTg T-cells, inhibiting aging-induced mitophagy (A) Quantification of mitophagy in young WT, old WT, and old 3xTg T-cells as assessed by Mtphagy dye staining. Results are presented as relative to old WT T-cells. Data are means ± SDs from 6 independent experiments (n = 6). ****p<0.0001. (B) Confocal images of young WT, old WT, and old 3xTg T-cells showing LC3 in green and Tom20 in red (left panel). Quantification of LC3-Tom20 colocalization is presented in right panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3).nsp > 0.05, *p < 0.05, ****p<0.0001. (C) Western blot of CerS6 and COXIV in the mitochondrial fractions of young WT, old WT, and old 3xTg T-cells (upper panel). Quantification showing increase in mitochondrial CerS6 in old WT T-cells, but not in young WT or old 3xTg T-cells in the bottom panel. Data are means ± SDs from independent experiments (Y: n = 3, 0, 3xTg: n=7).nsp > 0.05, *p < 0.05, ****p<0.0001. (D) Confocal images of old WT vs. old 3xTg T-cells showing CerS6 in green and Tom40 in red. Colocalization of CerS6 with Tom20 is higher in old WT T-cells compared to 3xTg T-cells. Quantification of colocalization in the bottom panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3). **p<0.01 (E) Mitochondrial levels of ceramides C14, C16, and dihydro(dh)-C16 as measured by LC-MS / MS lipidomics in young WT, old WT, young 3xTg, and old 3xTg T-cells. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, *p < 0.05, **p<0.01. (F) Confocal images of old WT vs old 3xTg T-cells showing Tom20 in green and ceramide in red (left panel). Quantification showing inhibition of ceramide interaction with TOM20 in right panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3). ***p<0.001. (G) Western Blot showing the overexpression of WT- and Mut-APP in Jurkat cells. Empty vector-transfected cells are used as a control. Actin is used as a loading control. (H-K) Confocal images of PLA results showing the interaction between APP-TOM20 (n=3) (H), CerS6-TOM20 (n=4) (I), and LC3- TOM20 (n=4) (J) in Jurkat cells transfected with EV, WT-APP that localizes to the mitochondria, or Mut-APP that does not localize to the mitochondria. PLA signal s / cell are quantified in K. Scale bars are equal to 10pm. Data are means ± SDs from independent experiments.nsp > 0.05, *p < 0.05, **p<0.01, ***p<0.001, ****p<0.0001. (L) List of proteins interacting with CerS6 upon pulling down the protein as determined by LC-MS / MS proteomics (Left Panel). Confirmation of ATAD3 interaction with CerS6 by immunoprecipitating CerS6 and blotting for ATAD3. Blotting for CerS6 is used as a loading control (Middle Panel). Quantification in right panel. (M) PLA of ATAD3 interaction with CerS6 showing an increase in ATAD3-CerS6 interaction in old T-cells compared to young and 3xTg T-cells (left panel). Right panel shows quantification of PLA signals / cell. Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, ****p<0.0001. (N, O) Mitophagy (N) and IFNv secretion (O) by young T-cells transfected with scr-siRNA or AT AD3 -siRNA and treated with SoSe during activation to induce mitophagy. Data are means ± SDs from 4 independent experiments (n = 4). **p<0.01. Figure 4. Metabolic changes in old WT T-cells are reversed in 3xTg T-cells (A, B) Metabolic profile of young WT vs old WT T-cells (A) or old WT versus old 3xTg T-cells (B) showing the decrease in tricarboxylic acid (TCA) cycle metabolites in old T-cells (A) that is reversed in old 3xTg T-cells (B), namely fumarate, malate, and argininosuccinate. Levels of metabolites were determined by LC-MS / MS total hydrophilic metabolome profiling and normalization by the Total Ion Count for every sample. Metabolomic results were acquired by Northwestern Metabolomic Core Facility and New York University Metabolomic Core Facility. Data are means ± SDs from

[0019] 3 independent experiments (n = 3). *p < 0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0020] Figure 5. Reconstitution of fumarate in old T-cells decreases mitophagy and restores T-cell function. (A-E) Effects of in vitro fumarate (20mM) treatment on activated old T-cell mitophagy and function. (A) Levels of mitophagy in old WT T-cells with or without fumarate (20mM) treatment in culture as measured by flow cytometry of Mtphagy dye. Data are means ± SDs from

[0021] 4 independent experiments (n = 4). ****p<0.0001. (B-D) Western blots of different mitochondrial proteins in old WT T-cells with or without fumarate treatment in vitro, namely ACO2 (n=3) (B), Tom40 (n=4) (C), and Tim23 (n=4) (D). Quantification of band intensities relative to actin shown in right panels. Data are means ± SDs from independent experiments. **p<0.01. (E) Fumarate treatment improves old CD8+ T-cell IFNy secretion as determined by flow cytometry. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, *p < 0.05, **p<0.01. (F-M) Effects of in vivo fumarate (lOmg / kg) treatment on activated old T-cell function. (F-J) Flow cytometry results showing improved T-cell viability (n=4) (F), IFNy secretion (n=4) (G, H), GZB secretion (n=5) (I), and lower IL 10 secretion (n=4) (J) by old T-cells that were collected from old mice treated with lOmg / kg fumarate for 2 months. Data are means ± SDs from independent experiments. *p < 0.05, **p<0.01, ****p<0.0001 (K) Tumor killing assay results showing the cell death of B16-F10 tumor cells cultured without T-cells (controls), or with T-cells from young WT mice, old WT mice, or old WT mice treated with fumarate. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, **p<0.01, ****p<0.0001. (L) Mitophagy levels in activated T-cells from WT young vs ASLKO young mice after exposure to 2pM SoSe, as assessed by Mtphagy dye fluorescence by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4). **p<0.01. (M, N) Heatmaps of NanoString nCounter results analyzed by nAnalyzer software showing RNAs whose significant increase in old T-cells is ameliorated upon treatment with in vitro fumarate (M) or showing RNAs that are impacted similarly upon fumarate treatment and in AD phenotype, when compared to old WT T-cells (N). Red boxes in (N) highlight genes that significantly change from young to old but are restored upon adding fumarate or AD T- cells. (0, P) Percentage (0) and mean fluorescence intensity (MFI) (P) of Foxp3+ Treg cells among CD4+ T-cells collected from young, old, and 3xTg mice after activation in vitro with or without the addition of 20mM fumarate. Data are means ± SDs from 5 independent experiments (n = 5). ***p<0.001, ****p<0.0001. (Q) Western blot of succination (2 SC) of immunoprecipitated Parkin from young, old, old + fumarate, or 3xTg T-cells showing decreased succination in old T- cells that is recovered in the 3xTg T-cells or upon treating with fumarate (left panel). Right panel shows the quantification of band intensities. Data are means ± SDs from 4 independent experiments (n = 4). ***p<0.001, ****p<0.0001. (R, S) Percentage of cells positive for Mtphagy dye (R) or IFNy (S) in old T-cells transfected with EV, WT-Parkin plasmid, or Mutant C431D Parkin plasmid. Data are means ± SDs from 4 independent experiments (n = 4).nsp>0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0022] Figure 6. AD phenotype and fumarate treatment restore aging T-cell functionality and effectiveness in Adoptive Cell Transfer (ACT) (A) Genotyping plot of the 3xTg APP transgene in Ctrl-Pmel versus 3xTg-Pmel mice. 3xTg mouse and Pmel mouse were used as positive and negative controls, respectively. (B) Western blot showing the increased levels of APP in 3xTg- Pmel mouse T-cells, but not in control mouse T-cells. APP KO mouse T-cells were used as a negative control. (C, D) Quantification of B16-F10 tumor size at endpoint (means + SEMs) (C) for each of the experimental groups in the adoptive cell transfer into recipient mice that were injected with T-cells from young Ctrl-Pmel mice, old Ctrl-Pmel mice, or old 3xTg-Pmel mice. One of the groups injected with old Ctrl-Pmel T-cells was also treated with lOmg / kg fumarate throughout the period of tumor monitoring. Tumor growth of each of the individual mice included in each group is shown in (D). **p<0.01, ***p<0.001. (E-G) Intracellular cytokine positivity levels of IFNy (n=4) (E) and GZB (n=4) (F), as well as levels of mitophagy (Mtphagy Dye) (n=6) (G) in TILs extracted from tumors from ACT experimental groups. Data are means ± SEMs from independent experiments. *p < 0.05, **p<0.01, ***p<0.001. (H) Mitotracker Red positivity of recipient T-cells after MitoTransfer from donor 3xTg T-cells labeled with Mitotracker Red, as measured by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4). ****p<0.0001. (I-K) PLA signals of APP-Tom20 colocalization (I), LC3-Tom20 colocalization (J), and CerS6-Tom20 colocalization (K) in Old recipient T-cells after MitoTransfer of mitochondria from young WT, old WT, or old 3xTg donor T-cells. Quantification of PLA signals / cell shown in the right panels. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3).nsp > 0.05, *p<0.05, **p<0.01, ****p<0.0001. (L) Mean Fluorescence Intensity of IFNy in MitoTransfer recipient old T-cells as measured by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4).nsp > 0.05, *p<0.05, ***p<0.001. (M) B16 tumor cell death was measured by Annexin V and Ghost Dye staining after co-culture with MitoTransfer recipient old Pmel T-cells and by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4).nsp > 0.05, **p<0.01, ***p<0.001. (N) B16-F10 tumor growth after adoptive transfer of old Pmel T-cells after MitoTransfer of mitochondria from young WT, old WT, or old 3xTg donor T-cells. Data are means ± SEMs from 3 independent experiments (n = 3). *p<0.05.

[0023] Figure 7. Human T-cells show similar metabolic defects and ceramide-dependent mitophagy signature with aging. (A) Metabolic profile of young (22yo) vs old (65yo) T-cells showing the decrease in tricarboxylic acid (TCA) cycle metabolites in old T-cells, namely fumarate, malate, and argininosuccinate. Levels of metabolites were determined by LC-MS / MS total hydrophilic metabolome profiling and normalization by the Total Ion Count for every sample. Metabolomic results were acquired by Northwestern Metabolomic Core Facility. Data are means ± SDs from 3 independent experiments (n = 3). *p < 0.05, **p<0.01, ****p<0.0001. (B) Levels of mitophagy (Mtphagy Dye) in CD4+ and CD8+ T-cells from 22yo versus 65yo with and without fumarate treatment as measured by flow cytometry. Data are means ± SEMs from 3 independent experiments (n = 3). **p<0.01, ***p<0.001, ****p<0.0001. (C) IFNy levels in T-cell supernatants as measured by ELISA, normalized to number of living cells in each well. Data are means ± SEMs from 8 independent experiments (n = 8). ****p<0.0001. (D-F) PLA results showing the interaction between LC3 and Tom20 (quantification to the right of images) (D) CerS6 and Tom20 (Quantification to the right of images) (E), and CerS6 and ATAD3 (Quantification to the right of images) (F) in 22yo versus 65yo T-cells with and without fumarate treatment. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3).nsp > 0.05, *p < 0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0024] Figure 8. Graphical abstract showing the role of APP and its product A 4O in inhibiting ceramide-dependent mitophagy and protecting anti-tumor function in aging AD T-cells. APP, and its product A04O, inhibit the AT AD3 -mediated shuttling of CerS6 from the ER to the mitochondrial membrane which normally occurs in aging T-cells (left panel). The inhibition of CerS6 localization to the mitochondria also inhibits the initiation of ceramide dependent mitophagy. This protects the fumarate levels in the aging AD T-cells, and the fumarate contributes to the inhibition of mitophagy as well as inducing transcriptional changes, possibly through protein / P ARKIN succination, to promote the anti-tumor function of the aging AD T-cells.

[0025] Supplemental Figure SI. T-cells of 3xTg mice, but not APP-PS1 mice, have a functional advantage and protect the mice from tumor growth and development. (A) Characteristics of AD cases and non-AD controls, 2016-2019 and 2021 Medical Expenditure Panel Survey (MEPS). Weighted proportions account for survey designs and weights. The ‘n’ represents the actual number of MEPS survey participants with AD diagnosis (AD cases) and without an AD diagnosis (non-AD controls) aged >60 years. The population sizes represent an approximate estimate of the number of individuals with the stated diagnosis and demographic characteristic in the United States. (B) List of diagnostic codes for ascertainment of cancer in the Medical Expenditure Panel Survey. Medical conditions reported by the MEPS respondent are recorded by the interviewer as verbatim text and then were coded to ICD-10-CM codes (ICD10 CDX) by professional coders. To preserve confidentiality, all of the conditions provided on the file are collapsed into 3 -digit diagnosis code categories rather than the fully specified ICD-10-CM code. (C) Images showing an example of tongue tumors on both young and old WT mice, all of which developed oral tumors, while none of the 3xTg mice developed oral tumors. (D) Ki67 immunohistochemistry staining of old WT tongue 4NQO-induced tongue tumors versus old 3xTg tongues, showing growth of tumor invading epithelial lining in the WT but not the 3xTg tongues (left panel). Quantification of Ki67 staining in right panel. Data are means ± SDs from 4 independent experiments (n = 4). ***p<0.001. (E) Multiplex staining of CD3 (red), CD8 (yellow), and Foxp3 (cyan) in tongues collected from old WT or old 3xTg mice exposed to 4NQ0 (left panel). Right panel shows the ratio of CD8+ T- cells to CD4+ Foxp3+ Tregs, demonstrating significantly elevated inflammatory environment in the 3xTg tongues, likely preventing tumor initiation. Data are means ± SDs from 4 independent experiments (n = 4). Non-parametric t-test *p<0.05. (F) Pictures of B16 subcutaneous tumors collected from old WT versus old 3xTg mice. (G) Percentage of CD3+ T-cells in the blood of mice treated with IgG or anti-CD3 antibody for T-cell depletion, showing the successful depletion of T- cells in the antibody treated group. Data are means ± SDs from 8 mice (n=8). ***p<0.001. (H) IFNy secretion by CD4+ (left panel) and CD8+ (right panel) T-cells collected from APP-PS1 AD mice versus their WT controls. Data are means ± SDs from 3 independent experiments (n = 3). ***p<0.001, ****p<0.0001.

[0026] Supplemental Figure S2. ATAD3 shuttles CerS6 to the mitochondria of aging T-cells and mitochondrial APP blocks this effect. (A) Levels of different ceramides in the mitochondria of T-cells collected from young WT, old WT, young 3xTg, or Old 3xTg as measured by LC-MS / MS lipidomics. Data are means ± SDs from 3 independent experiments (n = 3).nsp > 0.05, *p<0.05. (B) Percentage of positivity for Mtphagy dye fluorescence in T-cells collected from young WT vs CerS6' / _mice after activation in the presence of absence of 2pM SoSe. Data are means ± SDs from 4 independent experiments (n = 4). **p<0.01. (C) Percentage of positivity for intracellular IFNy cytokine in same T-cells as in (B). Data are means ± SDs from 4 independent experiments (n = 4). **p<0.01. (D) Western blot showing the overexpression of APP in young WT T-cells transfected with WT-V5-APP plasmid. Actin is used as a loading control. (E, F) Mitophagy (n=4) (E) and IFNy secretion (n=3) (F) by young T-cells transfected with EV or WT-APP overexpression plasmid and treated with SoSe during activation to induce mitophagy. Data are means ± SDs from independent experiments, *p < 0.05, ***p<0.001. (G) Western blot showing the successful downregulation of ATAD3 in scr-siRNA versus siATAD3A transfected WT T-cells from young WT mice. Actin is used as a loading control. (H, I) Confocal images of PLA experiments evaluating the colocalization of CerS6 and Tom20 (H) and Ceramide and Tom20 (I) in scr- versus si AT AD3 -transfected young WT T-cells activated in the presence of SoSe. Quantification of number of PLA signals / cell in bottom panels. Data are means ± SDs from 3 independent experiments (n = 3). ***p<0.001. (J, K) Confocal images showing the localization of PDI (Green) and TOM40 (Red) in scr- versus si AT AD3 -transfected young WT T-cells activated in the presence of SoSe, or young T-cells transfected with EV or WT-APP overexpression (OE) plasmid and treated with SoSe during activation (K). Quantification of colocalization coefficients shown in the right panels. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3). *p<0.05, ***p<0.001.

[0027] Figure S3. Ap40, but not A 42, is sufficient but not necessary to inhibit mitophagy in aging T-cells (A, B) PLA of Ap40 interaction with Tom40 (A) or A042 interaction with Tom40 (B) in WT vs 3xTg T-cells. Quantification of PLA signals / cell in right panels. Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, ****p<0.0001. (C) Levels of mitophagy in old T-cells treated with scr peptide, Ap40, or Ap42 during activation, as measured by Mtphagy Dye positivity by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4).nsp > 0.05, **p<0.01. (D) Confocal images of old T-cells treated with scr peptide, AP40 peptide, or AP42 peptide during activation showing Tom20 (green) and ceramide (red) colocalization. Quantification in lower panel. Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5). *p < 0.05 (E) PLA of Ap40 interaction with Tom40 upon adding exogenous Ab40 to old WT T-cells. Addition of Ab42 used as a negative control. Quantification of PLA signals / cell in the right panel. Scale bar is equal to 10pm. Data are means ± SDs from 5 independent experiments (n = 5).nsp > 0.05, ****p<0.0001. (F, G) Flow cytometry results showing activation markers CD25 and CD69 (F), as well as intracellular cytokines IFNy and IL10 (G) in young versus old T-cells treated with vehicle, Ap42, or Ap40 peptides. Data are means ± SDs from 3 independent experiments (n = 3). *p < 0.05, **p < 0.01, ***p < 0.001, ****p<0.0001. (H) B16 tumor cell apoptosis measured by Annexin V staining after co-culture with old Pmel T-cells treated with scr peptide, A04O peptide, or Ap42 peptide, measured by flow cytometry. Data are means ± SDs from 4 independent experiments (n = 4). *p<0.05. (I-J) Intracellular IFNy flow cytometry results in old WT vs old 3xTg T-cells treated with y-secretase inhibitor DAPT (I) or [3-secretase inhibitor (J) during activation. Data are means ± SDs from 3 independent experiments (n = 3). ***p<0.001, ****p<0.0001.

[0028] Supplemental Figure S4. Metabolic changes in old WT T-cells as measured by flux metabolomics. Flux metabolomic analysis of hydrophilic metabolites after activating young vs. old T-cells as described before. Addition of13C3-pyruvate (A) or13C3 -glutamine (B) to the T-cells during the final hour of activation allowed us to track the flux of the metabolic cycle in these cells. (A) Pyruvate entry into the TCA cycle via the condensation of acetyl-coA and oxaloacetate is not blocked, but a block in the progression of the TCA cycle can be seen at the level of a-ketoglutarate, with decreased levels of a-ketoglutarate, succinate, fumarate, and malate. (B) A block in the entry of glutamine into the TCA cycle can be seen, with decreased levels of a-ketoglutarate, succinate, and fumarate. Data shown are representative of three biological replicates.

[0029] Supplemental Figure S5. Fumarate supplementation reverses aging-induced mitophagy and transcriptional phenotype in old T-cells without affecting mouse behavior. (A) Western blot showing the levels of ACO2 in the T-cells collected from old mice treated with vehicle versus those treated with lOmg / kg fumarate (left panel). Quantification of the WB in the right panel. (B) Behavioral tests, rotarod (left panel) and Y-Maze (right panel) tests, performed on young versus old mice treated with vehicle of fumarate, demonstrating the nonsignificant effect of fumarate treatment on mouse behavior. Data are means ± SDs from 3 independent experiments (n = 3).nsp>0.05. (C) Fumarate levels in the serum of WT versus ASLKO mice. Data are means ± SDs from 4 independent experiments (n = 4). ***p<0.001. (D-F) RNA sequencing results from activated T-cells collected from young WT mice or 24 mo WT mice that had been treated with vehicle control or lOmg / kg fumarate for 2 months. (n=l for each group) (D) Heatmap showing the genes significantly changing from young to old, but then reversed upon treating the mice with fumarate. (E-F) Top significantly enriched pathways that include the genes that are significantly decreasing with age but recovered by fumarate (E) or the top significantly enriched pathways that include the genes that are significantly upregulated with age but inhibited by fumarate (F). (G) Western blot showing the expression of WT or mutant Parkin after transfection of old mouse T- cells. (H) PLA showing the interaction between Parkin and mitochondrial TOM20 in young, old, 3xTg, Old treated with fumarate, old transfected with WT-Parkin, or old transfected with mutant C431D Parkin T-cells (left panel). Right panel shows the quantification of the PLA signals / cell. Data are means ± SDs from 7 independent experiments (n = 7).nsp>0.05, *p<0.05, **p<0.01.

[0030] Supplemental Figure S6. Different therapeutic approaches utilizing superiority of 3xTg T- cells in resisting tumor growth and progression. (A) Graphical representation of the adoptive cell transfer (ACT) experiment carried out using Ctrl Pmel versus 3xTg Pmel T-cells. After crossbreeding the WT mice or the 3xTg mice with the Pmel mice, T-cells that specifically target melanoma tumors were collected from the hybrid progeny and activated in vitro using gplOO peptide, before reinjecting these mice via tail-vein injections into B6 mice bearing melanoma tumors on their flanks. (B, C) Multiplex staining of CD3+ and CD8+ T-cells infiltration into the tumors treated by adoptive cell transfer, showing a trend towards enhanced infiltration of the old 3xTg Pmel T-cells of the old Ctrl Pmel T-cells treated with fumarate systemically. Reduced tumor growth in Young T-cell and Old+Fum T-cell groups prevented the staining of more than one tumor in these groups. Data are means ± SDs. (D) Graphical representation of the MitoTransfer protocol used to transfer mitochondria from old 3xTg donor T-cells labelled with MitoTracker red into old WT recipient T-cells.

[0031] Supplemental Figure S7. T-cells from human AD patients with cancer show an increase in APP levels, a decrease in mitophagy, and an increase in cytokine production. (A) Western blot showing the levels of APP in PBMCs from age-matched patients, designated as APP-high versus APP-low. Quantification in right panel. Data are means ± SDs from 4 independent experiments (n = 4 individuals with pairs of age-matched donors). *p < 0.05. (B) Level of mitophagy in CD4+ and CD8+ T-cells collected from age-matched individuals with either high levels of APP or low levels of APP. Data are means ± SDs from 4 independent experiments (5 technical replicates for 4 pairs). **p < 0.01. (C) qPCR results quantifying the levels of TFNy mRNA in PBMCs taken from cognitively healthy versus AD patients with cancer. Data are means ± SDs from 8 independent experiments (n = 8 individuals with AD and cancer and 8 age-matched individuals with matched cancer type). *p < 0.05. (D) Tri-color confocal images of Head and Neck Cancer tumor tissues from age-matched cognitively healthy versus AD patients showing CD3+ T- cells in blue, Tom40 in red, and LC3 in green. Tom40-LC3 colocalization was visualized in CD3+ TILs (Merge images) and quantified in right panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3 individuals with AD and cancer and 3 age-matched individuals with matched cancer type). *p < 0.05 (E) Combination of immunofluorescence and PLA showing CD3+ TILs (green) in same Head and Neck Cancer tumor tissues as above, and APP-Tom20 colocalization in these TILs by PLA. Quantification of PLA within CD3+ TILs in bottom panel. Scale bar is equal to 10pm. Data are means ± SDs from 3 independent experiments (n = 3 individuals with AD and cancer and 3 age-matched individuals with matched cancer type). *p < 0.05. (F) Confocal images of same tumor tissues as above showing CD3+ TILs in green, and succination in red using an anti-2SC antibody. Quantification of succination signal from within CD3+ TILs in bottom panel. Scale bar is equal to 10pm. Data are means ± SDs from 4 independent experiments (n = 4 individuals with AD and cancer and 4 age-matched individuals with matched cancer type). *p < 0.05.

[0032] DETAILED DESCRIPTION OF THE INVENTION

[0033] It is to be understood that the descriptions of the present invention have been simplified to illustrate elements that are relevant for a clear understanding of the present invention, while eliminating, for the purpose of clarity, many other elements found in typical pharmaceutical compositions. Those of ordinary skill in the art will recognize that other elements and / or steps are desirable and / or required in implementing the present invention. However, because such elements and steps are well known in the art, and because they do not facilitate a better understanding of the present invention, a discussion of such elements and steps is not provided herein. The disclosure herein is directed to all such variations and modifications to such elements and methods known to those skilled in the art. Furthermore, the embodiments identified and illustrated herein are for exemplary purposes only, and are not meant to be exclusive or limited in their description of the present invention.

[0034] Studies have shown that AD patients exhibit lower cancer incidences than their age-matched non- AD counterparts. The data demonstrated that preventing aging-stress-mediated and ceramidedependent lethal mitophagy by APP and A04O in T-cells enhances their anti-tumor functions to control tumor growth in 3xTg AD mice compared to controls. Mechanistically, these studies revealed that APP-TOMM complex interaction at the outer mitochondrial membrane attenuates CerS6 trafficking to mitochondria by ATAD3 in aging AD T-cells, preventing ceramidedependent mitophagy. This then leads to restoring mitochondrial fumarate metabolism and protein succination, improving anti-tumor functions of AD T-cells in culture and in vivo using ACT-based immunotherapy. The data also showed that exogenous fumarate supplementation or healthy AD mitochondria transfer functionally mimics AD-APP phenotype in aging T-cells, enhancing their anti-tumor activity to control tumor growth in situ and in vivo, including ACT (Figure 8). These data are also consistent in human T-cells, in which T-cells isolated from aging donors showed elevated mitophagy with fumarate depletion, restored in T-cells isolated from age-matched AD patients. These data support a new hypothesis that improved tumor control in AD mice and humans depends mainly on APP / Ap40-mediated protection against ceramide-dependent mitophagy and fumarate depletion in AD T-cells for enhanced anti-tumor functions.

[0035] The roles of mitochondrial accumulation of APP and its processing in inhibiting mitophagy in AD neurons have been well studied previously50,51’53’77. However, whether mitochondrial APP plays any role in T-cells has not been demonstrated previously. The inventors show that mitochondrial APP inhibits CerS6 trafficking to mitochondria in AD T-cells, attenuating ceramide-dependent lethal or hyperactive mitophagy. CerS6 / C14-ceramide mitophagy inhibition improves aging AD T-cells’ anti-tumor functions, enhancing tumor killing in co-culture studies and ACT-based immunotherapy in mice. The inventors have also demonstrated that depletion of T-cells using an anti-CD3 antibody almost completely abrogated suppression of tumor growth in 3xTg AD mice. The connection between AD and T-cell function has been studied in the context of neuronal signaling and AD pathology9'12. However, the roles of APP and A|140 in improving anti-tumor functions of T-cells have not been described previously. The reason A042 does not show similar protective effects as AP40 on T-cell mitophagy remains unknown, especially since both A04O and A042 have been shown to increase in the plasma of aging 3xTg mice78. The studies suggest that Ap42 does not interact with the TOMM complex, which seems to be essential for CerS6 trafficking to mitochondria.

[0036] Interestingly, some clinical studies have shown that increased levels of plasma Ap40, but not A042, significantly correlate with a heightened risk of AD79’80. Other studies describing the involvement of A0 peptides in disrupting mitochondrial function77have also directly implicated A04O specifically in the impairment of mitochondrial function81’82. This agrees with the findings of the inventors, suggesting that the increased plasma Ap40 levels in AD patients can potentially contribute to the inhibition of ceramide-dependent mitophagy in their T-cells, ultimately protecting those T-cells against aging-induced defects in anti -turn or function.

[0037] The inventors’ recently published data26showed that aging stress induces CerS6 / C14-ceramide accumulation in mitochondria, which then recruits autophagosomes to degrade mitochondria through LC3 -ceramide association, suppressing anti -turn or functions of aging T-cells, leading to increased tumor growth. However, how CerS6 is recruited to mitochondria in response to aging stress in T-cells was unknown. The inventors demonstrate that ATAD3 plays a vital role in the mitochondrial trafficking of CerS6 from ER in aging T-cells. ATAD3 is known to mediate ER- mitochondrial contacts, which then allows the bi-directional trafficking of proteins between ER and mitochondria70. Previous studies showed that ATAD3 regulates mitochondrial cristae architecture83and removal of mitochondrial DNA84. These data were also consistent in AD T- cells, as mitochondrial CerS6 and C14 / 16-ceramide generation in the AD T-cell mitochondria were attenuated by decreased ATAD3-CerS6 interaction in T-cells isolated from 12 mo 3xTg compared to WT mice. Ectopic expression of APP inhibited ATAD3 function, reducing the number of mitochondria-ER contact sites upon mitophagy induction. One of the metabolic signatures of ceramide-dependent mitophagy in aging neurons is the depletion of malate and fumarate66. This study also detected malate and fumarate depletion in aging T-cells compared to younger mice or human T-cells. Restoring fumarate levels in aging T- cells prevented ceramide-dependent mitophagy. It improved their anti-tumor functions in coculture studies or ACT-based immunotherapy in vivo, functionally phenocopying aging AD T- cells for improved control of tumor growth. Although the mechanism by which fumarate inhibits ceramide-mediated mitophagy in aging T-cells is unclear, its role in protein succination might be involved76. While previous studies have shown the inhibitory effects of fumarate on T-cell function85’86, these studies examined fumarate treatment of young T-cells, where ceramidedependent hyperactive mitophagy is absent. For example, one of these studies implicates the succination of Zap70 by cancer cell-generated fumarate, which has been reported to suppress the anti-tumor capacity of CD8+ T-cells in the tumor microenvironment83. It is essential to mention that there are stark differences between young and aging T-cells, especially when it comes to the different levels of ceramide-dependent mitophagy, which might explain this difference in the response to fumarate between young and aging T-cells. For example, the succination of proteins essential for inducing ceramide-mediated mitophagy, such as Parkin, might inhibit mitophagy in aging T-cells, which supports their anti-tumor activity. Fumarate also seemed to significantly decrease Foxp3 transcription and Treg induction in the aging T-cells, which might also result from other epigenetic effects via the succination of transcription factors. Another resultant of the transcriptional changes induced by fumarate is the restoration of stearoyl-CoA-desaturase 1 (SCD1) levels upon adding fumarate. SCD1 is a crucial enzyme of lipid metabolism87, and its downregulation has been associated with an increase in lethal ceramide biosynthesis in colorectal cancer cells88. The decrease in SCD1 expression in aging T-cells might yield a similar effect, contributing to the hyperactive ceramide-dependent mitophagy, and this effect might be blocked by fumarate as well as in the AD T-cells. The possible role of Scdl in this mechanism needs to be further studied. However, the role of the succinated proteome in aging T-cells, especially as it relates to mitophagy and transcriptional or metabolic regulation, must be identified and studied in more detailed experiments, and the specific differences in response to fumarate between young and aging T-cells also need to be further examined. The invention has important biological and therapeutic implications. For example, exogenous fumarate as a supplement improved aging T-cells’ anti-tumor functions in ACT-based immunotherapy by protecting the aging T-cells against mitochondrial damage and hyperactive ceramide-dependent mitophagy. To this end, when aging T-cells were implanted with AD mitochondria89, isolated from AD T-cells, which are protected against ceramide-dependent mitophagy by mitochondrial accumulation of APP, their anti-tumor activity was enhanced, suggesting that the transfer of healthy mitochondria into aging T-cells could be a new therapeutic strategy for improving tumor control by T-cells. In another embodiment, expressing non- pathogenic APP or A04O in aging T-cells to inhibit ceramide-dependent mitophagy and enhance their anti-tumor functions is possible. Inhibition of CerS6 or its trafficking to mitochondria by targeting ATAD3 could also attenuate mitophagy and help control tumor growth in aging T-cells.

[0038] Although the inventors have established a mechanistic link between mitophagy inhibition in aging AD T-cells and the protection of their anti-tumor function, some limitations must be discussed. While the 3xTg mouse model used in the study is a commonly used AD model in multiple studies of APP and amyloid , the expression of two other transgenes (MAPT P301L and PSEN1 M146V) may act as a confounding variable63. However, the focus on APP stemmed from the well- established role of APP in mitophagy inhibition47’48’53’54, as well as its clear expression in T-cells, as shown in multiple studies59’60. Besides, to address this, the inventors performed several in vitro studies, specifically overexpressing APP, to delineate its role in enhancing aging T-cell anti-tumor function by inhibiting the ATAD3-mediated shuttling of CerS6 to the mitochondria. Besides, the inventors’ studies using amyloid 0 were conducted by treating WT T-cells with the different A0 peptides, which allowed the inventors to derive conclusions about the A0 peptides' specific impact on T-cell function without other genetic interventions. These studies showed the role of APP and its product A04O in inhibiting aging-induced ceramide-dependent mitophagy and improving antitumor function in aging T-cells. The inventors have shown that the anti-tumor function of both CD8+ and CD4+ T-cells benefited from inhibiting ceramide-dependent mitophagy either by overexpressing APP or supplementing with fumarate. In the ACT studies, mainly CD8+ cytotoxic T-cells from the transgenic Pmel mice are activated against B16 melanoma tumor cells26’90, and the enhancement of CD8+ T-cell antitumor function in the AD T-cells or upon treating with fumarate is evident from the protection of those groups against tumor growth. On the other hand, data demonstrating reduced Foxp3 expression levels in the AD T-cells or upon fumarate supplementation mainly addresses CD4+ T- cells (the inventors focused on CD4+ T-cells in the gating strategy). Although the impact of interventions on both CD4+ and CD8+ T-cells were shown, some of the in vitro data do not distinguish between the two cell types.

[0039] Overall, the inventors have discovered a new mechanism by which AD-associated APP and A04O play critical roles in improving anti-tumor functions of T-cells by preventing ceramide-mediated mitophagy in aging AD T-cells, which, in part, helps explain the clinical data demonstrating lower cancer incidences in AD patients compared to age-matched non-AD counterparts. Moreover, data obtained from this work will also help design new therapeutic strategies, like fumarate supplementation or healthy mitochondria transfer, to phenocopy AD T-cells in aging non-AD T- cells to enhance their tumor cell killing by inhibiting aging-stress mediated mitochondrial dysfunction.

[0040] Thus, in one embodiment of the invention, provided is a method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of overexpressing Alzheimer’s disease-associated APP in the T-cells.

[0041] In another embodiment of the invention, provided is a method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of treating the T-cells with exogenous A 4O. In a further embodiment of the invention, provided is a method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of treating the T-cells with fumarate.

[0042] In a still further embodiment of the invention, provided is a method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of transferring mitochondria from AD T-cells to non-AD T-cells.

[0043] EXAMPLES

[0044] The following examples further describe and demonstrate particular embodiments within the scope of the present invention. Techniques and formulations generally are found in Remington's Pharmaceutical Sciences (Mack Publishing Co., Easton, Pa.). The disclosure is further illustrated by the following examples, which are not to be construed as limiting this disclosure in scope or spirit to the specific procedures herein described. It is to be understood that the examples are provided to illustrate certain embodiments and that no limitation to the scope of the disclosure is intended thereby. It is to be further understood that resort may be had to various other embodiments, modifications, and equivalents thereof which may suggest themselves to those skilled in the art without departing from the spirit of the present disclosure and / or scope of the appended claims.

[0045] Materials availability

[0046] All stable reagents generated in this study are available from the Lead Contact with a completed Materials Transfer Agreement. RRID numbers for antibodies and details of biological samples, mice strains and commercial assays used in this manuscript are listed in the Key Resources Table (Supplementary Materials).

[0047] Data and code availability

[0048] The RNA sequencing data generated during this study are available at Gene Expression Omnibus (GEO) with the accession number GSE247335. The NanoString data generated during this study are available at GEO with the accession number GSE248924. Original western blot images have been deposited at Mendeley and are publicly available as of the date of publication. The DOI is listed in the key resources table. Microscopy data reported in this paper will be shared by the lead contact upon request.

[0049] Animals

[0050] Animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) at the Medical University of South Carolina.

[0051] Mice and tumor models

[0052] Vertebrate animals were maintained in pathogen-free facilities. Experimental procedures were performed using protocols approved by the Institutional Animal Care and Use Committee (IACUC) at the Medical University of South Carolina. C57BL / 6I, B6129SF2 / J, 3xTg, APP-PS1, and Pmel mice were obtained from Jackson Laboratory (Bar Harbor, ME). 3xTg-Pmel and CtrL Pmel mice were developed in the lab. Pmel+ mice were employed for melanoma studies. The animals were maintained in-house for 2-3 months (young) or 12-18 months for the aging stress condition. 4NQ0 was used to induce the incidence of endogenous head and neck oral squamous cell carcinoma tumors. B16-F10 cells were injected subcutaneously for the induction of an exogenous melanoma model.

[0053] 4NQO tumor model

[0054] Mice, including 2-3mo WT, 12mo WT, and 12mo 3xTg mice, were treated with 4-NQO at 40 pg / mL in drinking water for 16 weeks. After carcinogen treatment, all animals were changed to regular drinking water for 8 weeks. After the 8 weeks, animal tongues were monitored for tumor growth using a Nikon SMZ18 stereo microscope. At the endpoint, mice were euthanized, and autopsy was performed, with tongues excised and all tongue tumors carefully examined for number and size. Tongue tumors and normal tissues were fixed in 10% buffered formalin and embedded in paraffin blocks for histological evaluation. Diagnosis of tongue tumors using hematoxylin and eosin (H&E) stained sections was conducted by a trained pathologist at MUSC.

[0055] B16 subcutaneous injection model and CD3 depletion Mice (WT or age-matched AD mice) were injected with 300,000 B16-F10 cells into the flank subcutaneously, and tumor growth was then monitored and measured with digital calipers. In one experimental group, CD3+ T-cells were depleted from 3xTg mice using an / / dvvoMAb anti -mouse CD3 antibody (BioXCell). Beginning two days before B16 cell tumor implantation, mice were treated with an intraperitoneal injection of an initial dose of 200 pg / mouse of the anti-CD3 antibody in PBS, followed by similar dosing with 100 pg / mouse every other day throughout tumor growth. Control groups were treated with ZuEzvoMAb rat IgG2b isotype control anti-keyhole limpet hemocyanin (BioXCell).

[0056] Isolation of Tumor-infiltrating Lymphocytes (TILs)

[0057] To obtain tumor-infiltrating T-cells (TILs) from subcutaneously established stable B16-F10 melanoma-bearing mice, tumors were excised, chopped finely using tweezers and scissors, and then mechanically dissociated using the bottom end of a syringe-plunger. Following dissociation, tumors were filtered through 70mMcell strainers (BD Biosciences, San Jose, CA). The cell suspension was washed in a culture medium twice by centrifugation at 1500 rpm for 10 min at 4°C. After the second wash, the cells were resuspended in 4mL PBS and layered carefully over 4mL Ficoll-paque (GE Healthcare), followed by centrifugation at 1,500 rpm for 30 min with 0 acceleration and deceleration. The enriched TILs obtained at the interface as a thin buffy coat layer were washed with PBS twice and resuspended in FACS staining buffer for further downstream procedures.

[0058] Behavioral studies in mice. Accelerated Rota Rod test: The mice were placed in the rotating cylinder twice daily for three days. Each trial lasts a maximum of 10 min, during which the rotating rod accelerates from 4 to 40 rpm over the first 5 min of the trial and then remains at maximum speed for the remaining 5 min. Animals rested for at least 10 min between trails to avoid fatigue and exhaustion. Novelty Preference test (Y-maze): This test included two trials. During Trial 1, one of the arms of the Y-maze was blocked, allowing for a 3 -minute exploration of only two arms of the maze. After a 1 min delay, Trial 2 started. During Trial 2, all three arms were available for another 3 min of exploration. Trial 2 took advantage of the innate tendency of mice to explore novel unexplored areas (e.g., the previously blocked arm). The time spent in novel unexplored regions of each animal was measured. Mice with intact short-term memory prefer to explore a novel arm over the familiar arms, whereas mice with impaired episodic memory enter all arms randomly.

[0059] Mouse Genotyping

[0060] DNA was extracted from mouse tail clips by heating the tail clips at 95°C in 50 mM NaOH for 10 minutes. IM Tris (pH 8.0) was added to the tail clips, and the supernatant was used for downstream genotyping applications. To assess the presence of the APP transgene, probes designed to target the APP transgene versus WT APP specifically were conjugated to a fluorophore / quencher combination and used in a probe-PCR reaction, as recommended by The Jackson Laboratory genotyping protocols. As for the presence of the Pmel transgene, PCR was performed under standard conditions described by Ji et al.93.

[0061] Primers used were Pmel-Fl : ctttagacctccggcactgttgc; Pmel-Rl : gcaagtagcagtgtatcaaatatgc; PmelTCR-Rl : gtagctttgtaaggctgtggagag. Pmel-Fl and Pmel-Rl amplify a transgenic band of 308 bp. CPmel-Fl and TCR-R1 amplify an endogenous band of 203 bp.

[0062] Adoptive T-Cell Transfer

[0063] T-cells were isolated from young or old Ctrl-Pmel mice or old 3xTg-Pmel mice, then activated in vitro with gplOO peptide as described earlier. Meanwhile, B16-F10 tumors were implanted in C57BL / 6J mice, as described above. When tumors were visible, the melanoma-bearing mice were injected intravenously by tail vein injection with the activated T-cells, which specifically target the B 16 cells. Tumor growth was then monitored and measured using digital calipers. In one group (injected with Ctrl-Pmel T-cells from old mice), the mice were treated with 20mg / kg fumarate every other day throughout tumor monitoring. At the endpoint, tumors were collected and processed into TILs as described elsewhere or formalin-fixed / frozen for different downstream applications (described elsewhere). Cell Lines and Culture Conditions

[0064] B16-F10 (RRID: CVCL 0159) was obtained from the American Type Culture Collection (ATCC) suggested to be of male origin. M0C2 (RRID:CVCL ZD33) was obtained from Kerafast, and it was derived from a chemokine receptor CXCR3 deficient female mouse on a pure C57BL / 6 background. B16 mouse melanoma cancer cells were grown in RPMI containing 10% FBS and 1% penicillin / streptomycin. MOC2 mouse head and neck cancer cells were grown in DMEM containing 10% FBS and 1% penicillin / streptomycin. Jurkat cells (clone E6-1, RRID:CVCL_0367) were obtained from ATCC and were grown in RPMI containing 10% FBS and 1% penicillin / streptomycin.

[0065] In Vitro T-cell activation

[0066] Naive total T-cells were purified from the total splenocytes of 8-72week-old 3xTg mice (B6;129- Tg (APPSwe,tauP301L)lLfa PsenltmlMpm / Mrnjax) and their background-matched WT controls (B6129SF2 / J), or APP-PS1 (B6.Cg-Tg(APPswe,PSENldE9)85Dbo / Mmjax), CerS6-A, or ASLKO and their background-matched WT controls (C57BL / 6J). This was achieved by negative selection using Dynabeads™ Untouched™ Mouse T Cells Kit (Invitrogen), which contains a cocktail of rat IgGs that bind mouse B cells, NK cells, monocytes / macrophages, dendritic cells, erythrocytes, and granulocytes, which are then bound by magnetic beads which are separated from the T-cells using a magnet. In studies assessing Foxp3+ Treg induction, anti-CD25 antibody was added to the depletion cocktail to deplete natural Tregs. Hybrid Ctrl-Pmel and 3xTg-Pmel transgenic mice were also used. Within experiments, mice were age and sex-matched.

[0067] Purified mouse T-cells were then activated using plate-bound anti-CD3 (2pg / ml) and anti-CD28 (5pg / ml) antibodies in the presence of lOOIU / ml IL-2. For Pmel TCR transgenic mice, splenocytes were stimulated with 1 mg / ml gplOO melanoma antigen in the presence of 100 lU / ml IL2. Cells were differentiated for three days in IMDM media supplemented with 10% FBS, 4mM L- glutamine, 100 U / ml penicillin, 100 mg / ml streptomycin, 55 mM beta-mercaptoethanol under 5% CO2, atmospheric oxygen at 37°C in a humidified incubator. In some experiments, T-cells were activated in the presence of 20 mM fumaric acid to assess its effect on T-cell function. To evaluate intracellular cytokines by flow cytometry, the inventors re-stimulated T-cells with PMA / ionomycin for 4 h or with anti-CD3 (2 mg / ml) and anti-CD28 (5 mg / ml) overnight in the presence of Golgi inhibitors.

[0068] Flow Cytometry (Intracellular flow cytometry + surface staining + viability)

[0069] Staining for cell surface markers was performed by incubating cells with the antibody at 1 : 100 dilutions in FACS buffer (1% BSA, 0.05% Sodium Azide in PBS) for 20 min at 4“C in the dark. For intracellular cytokines (IFNy, IL4, IL10, IL17A, GZB, TNFa) staining, surface markers were stained before fixation / permeabilization (BD Cytofix / Cytoperm Kit, BD Biosciences, San Jose, CA). Cells were then incubated with the antibodies for 30 minutes at 4 'C in the dark. For FoxP3 staining, surface markers were stained before fixation / permeabilization (eBioscience™ Foxp3 I Transcription Factor Staining Buffer Set), and cells were then incubated with the anti-FoxP3 antibody for 30min at 4°C in the dark. Living cells were identified using Ghost Dye™, which irreversibly binds intracellular free amines exposed in cells with compromised cell membranes. Samples were acquired on LSR Fortessa / X-20 and analyzed with FlowJo software (Tree Star, OR). All analyses were performed on living cells (Ghost Dye™ negative).

[0070] Polyclonal Tumor Killing Assay

[0071] For in vitro tumor-killing assays, splenocytes from mice with different ages and backgrounds were exposed to the supernatants from either B 16-F 10 or MOC2 cell lines. Supernatants were collected from cell culture dishes and then centrifuged to remove floating cells and debris. The supernatants containing epitopes from the cultured cells were then added to the splenocytes and left for a week for antigen-presenting cells to pick up the antigens and present them on their surface to the T-cells. A week later, the tumor cells of interest (Bl 6-F 10 or M0C2) were stained using a proliferation dye (CellTrace™, Thermofisher) and co-cultured with the activated T-cells for 24 hours. After coculturing the cells, they were stained by Ghost Dye™ for 10 minutes at 4" C in the dark, after which they were stained with Annexin V (BD Biosciences) as per the manufacturer’s protocol. Briefly, cells were incubated with Annexin V in Annexin V binding buffer for 15 minutes, after which they were acquired using LSR Fortessa / X-20. Cells that were positive for both Ghost Dye™ and Annexin V were considered dead cells, while cells that were only Annexin V positive were considered apoptotic cells.

[0072] Plasmids and transfections

[0073] Naive T-cells were isolated from spleens, then transfected with plasmids or siRNA using the Lonza AmaxaTM mouse T cell nucleofector™ kit following manufacturers’ protocol. Transfected cells were then activated as described in the corresponding section for 72 h. Plasmids used include a V5-APP overexpression plasmid and empty vector plasmid, while siRNA included ATAD3 Silencer® siRNA and scrambled (scr) siRNA (Thermofisher).

[0074] Site-directed mutagenesis

[0075] Primers were designed based on the coding sequence of the canonical gene of interest. The coding sequence was converted into the amino acid codon sequence using Expasy to quickly mutate the amino acid(s) of interest. About 15-20 amino acids upstream and downstream of the mutated codon were selected, and the New England Biolabs Tm Calculator was used to adjust the primer length, projected annealing temperature, and GC content. The Harvard Reverse Complement Tool was used to produce the reverse primer sequence. Primers were ordered from Integrated DNA Technologies, including 5 ’-phosphorylation for plasmid ligation. The template plasmid (containing the wild-type gene of interest for mutation) and the primers were then used with the QuikChange XL Site-Directed Mutagenesis kit (Agilent Technologies, #200516) per the manufacturer’s instructions. The successful mutation was confirmed via sequencing of the plasmid (Genewiz, Azenta Life Sciences)34.

[0076] Immunoblotting

[0077] Activated T-cells were homogenized in RIPA buffer (25 mM Tris-HCl pH7.4, 150mM NaCl, 1% Triton X- 100,1% sodium deoxy cholate, EDTA (20 pl Of 0.5M stock)) including protease inhibitor and phosphatase inhibitor cocktails using a 28.5 G syringe five times the incubated for 20 minutes on ice. The samples were centrifuged at 16,000 g for 10 minutes at 4°C. The supernatants were collected, and proteins were quantified using the Bicinchoninic acid (BCA) (Pierce, Rockford, IL) method. 6X loading dye was added to the sample and boiled using a heating block at 95 degrees for 10 minutes before loading the samples on SDS gradient gels 4%-20% and running them using the Bio-Rad Criterion apparatus, followed by semi-dry transfer onto PVDF membranes. Blocking was done with 3% Bovine Serum Albumin (BSA) in PBS with 0.1% Tween-20. Primary antibodies were used at 1 :1000 dilution overnight at 4°C. Horseradish peroxidase (HRP)-conjugated secondary antibodies against mouse or rabbit IgG were added to the membranes in 5% milk (1 :10,000 dilution) for 1 hour at room temperature. Enhanced chemiluminescent (ECL) horseradish HRP substrate was then added to the membranes to visualize the proteins of interest using the ChemiDoc imaging system. Proteins of interest included ACO2, Tom20, CerS6, Tim23, Tom40, and actin and COXIV as loading controls for total cell lysates and mitochondrial fractions, respectively.

[0078] Mitochondrial Fractionation

[0079] Mitochondrial isolation from 107T-cells was performed by differential centrifugation as described by Kim et al.89. Briefly, cell pellets were homogenized using a disposable 1 ml syringe in SHE buffer [0.25 M sucrose, 20 mM HEPES (pH 7.4), 2 mM EGTA, 10 mM KC1, 1.5 mM MgC12 and 0.1% defatted bovine serum albumin (BSA)] containing a protease inhibitor (Roche Diagnostics, Mannheim, Germany) and centrifuged at l,100xg for 3 min at 4°C (to remove unbroken cells and cell debris). The supernatant was centrifuged at 12,000xg for 15 min at 4°C to pellet mitochondria. The supernatant containing the cytoplasmic fraction was removed and kept on ice. The mitochondrial pellet was resuspended in 500pl of the SHE buffer and centrifuged at 20,000xg for 10 min at 4°C, after which the supernatant was removed. The pellet was resuspended and centrifuged at 20,000 x g for 5 min at 4°C. After removal of the supernatant, the pellet was resuspended in 50pl of RIP A buffer and kept on ice until measurements were performed. Isolated mitochondria were quantified by determining the protein concentration using a bicinchoninic acid (BCA) assay (Pierce, Rockford, IL). Mitochondrial and cytoplasmic fractions were then run on a gel for immunoblotting, as described before. All assays were performed with freshly isolated mitochondria. Immunofluorescence

[0080] Activated cells were incubated with the respective treatment then washed two times with 1XPBS. Cells (50,000 per well) were fixed and permeabilized using 4% paraformaldehyde (15 min) and 0.4% Saponin in IxPBS (pH 7.4) for 15min each. The cells were then blocked with 5% BSA in PBS (pH 7.4) for 1 h. Cells were incubated for 18 h at 4°C with antibodies (1 :100) specific to Ceramide, LC3, Tom20, Tom40, CerS6, APP, Ab40, Ab42, and PDI in blocking solution, followed by Alexa Fluor 488-, 594-, or 633 -conjugated secondary antibodies (1 : 1000) an additional hour at room temperature.

[0081] For confocal microscopy imaging, poly-L-lysine coated 35-mm glass-bottomed dishes (MatTek Corporation) were treated with Cell Tak compound at RT for Ih, followed by 5 washes with ddiH20 without allowing coverslips to dry until cells were loaded. Fixed T-cells were loaded on the treated coverslips and observed using the Olympus FVlOi confocal microscope. A humidifier chamber was employed to acquire images of these cells.

[0082] FFPE slides were deparaffmized and rehydrated through a series of xylene and ethanol washes for paraffin-embedded tissues. Heat-induced epitope retrieval was performed for 30 minutes at 95°C. After primary antibody incubations (overnight at 4°C), slides were incubated with secondary antibodies conjugated to Alexa Fluor 488 or 594 for 1 hour at room temperature, then imaged using the Olympus FVlOi confocal microscope.

[0083] For frozen slides, slides were first fixed in acetone at -20°C for 20 minutes after thawing, then rehydrated in PBS for 15 minutes. Slides were then treated as described above for immunostaining.

[0084] Proximity Ligation Assay

[0085] Proximity ligation assays were performed using Duolink in situ red kit (Sigma) per the manufacturer’s instructions. Briefly, T-cells were fixed with 4% PFA for 15 minutes, then permeabilized with 0.1% Triton X for another 15min at room temperature. The PLA blocking agent was then used to block non-specific binding, and the cells were incubated overnight in the presence of antibodies of interest. After washing, secondary PLA probes conjugated to oligonucleotides were added to the cells, and then a ligase was added to the samples to ligate the oligonucleotides that are in proximity. DNA rolling-circle amplification was then performed using the PLA polymerase in the presence of fluorescence-bound oligonucleotide probes, yielding a fluorescent signal only where the two targets of interest were interacting in proximity. Cells were imaged using the Olympus FVlOi laser scanning confocal microscope. Signal quantification was performed using the Duolink in Situ Image Tool software as described previously91. Tissues were prepared as described in the Immunofluorescence section, but the PLA protocol was then followed instead of the IF protocol.

[0086] Detection of Mitophagy by Mtphagy Dye Staining

[0087] T-cells were stained with Mtphagy Dye (Dojindo) for 30 minutes at 37°C before starting activation. When mitophagy is induced, the damaged mitochondria fuse to lysosomes, after which Mtphagy Dye emits a high fluorescence. After 72 hours of activation, T-cells were collected and stained with a live / dead Ghost Dye™ to identify living cells, and fluorescence in the living cells was measured by flow cytometry.

[0088] Sphingolipid measurement by lipidomics

[0089] Cells were collected and washed twice with cold PBS. Further preparation of samples and measurement of endogenous ceramides by LC-MS / MS followed the protocol described previously26,34’92. Briefly, samples were supplemented with internal standards and 2mL of isopropyl alcohol: water: ethyl acetate (30:10:60; v:v:v) was added to the extracts. Samples were subjected to two rounds of vortex and sonication followed by 10-min centrifugation at 4,000 rpm. The supernatant or top layer was used as lipid extract and subjected to LC-MS / MS for analysis of ceramide species. The MUSC Lipidomics Shared Resources performed lipid extraction and analyses. Inorganic phosphates (Pi) were used for normalization.

[0090] Immunoprecipitation Cells were lysed using immunoprecipitation (IP) buffer, and precleared fractions were incubated overnight with 2pg of corresponding antibodies at 4°C, followed by 1-hour incubation with Pierce™ Protein A / G Magnetic Beads (50 pl of beads). The resin was washed three to five times, and then SDS-PAGE analyzed pulled-down proteins. Gels were either transferred onto Western Blots as described before and probed with antibodies of interest, or gel bands of interest were collected and shipped for proteomic analysis by LC / MS / MS at the Taplin Mass Spectrometry Facility (Harvard).

[0091] Mitophagy induction in young T-cells (SoSe)

[0092] To simulate aging stress and mitophagy induction in young T-cells, T-cells were first isolated from 2-3 months old mouse spleens and then activated for 72 h as described in the corresponding section. For the final 24 hours of activation, T-cells were exposed to 2pM of sodium selenite (SoSe) to induce mitophagy as described before34’66.

[0093] Ap40 vs A 42 treatment

[0094] T-cells were activated as described above in the presence of 5 M A|340 or 5 M A|342 (rPeptide) for 72 h, then collected and analyzed. To assess the role of APP processing in aging AD T-cell function, T-cells were activated in the presence of increasing doses of the y-secretase inhibitor (DAPT) or a -secretase inhibitor (LY2886721) for 72 h, then collected and analyzed.

[0095] Steady-state metabolite profiling and targeted metabolic flux analysis

[0096] After 72 hours of activation, cells were rinsed with an ice-cold standard saline solution, and the plates were put on dry ice. One mL of 80% methanol (-80°C) was added. After scraping the plates on dry ice, the cell lysate / methanol mixture was frozen in liquid nitrogen and lysed by three freezethaw cycles between -80 and 25°C. Samples were stored at least 4 hours at -80°C before the centrifugation at 20,000 x g for 15 mins at 4°C. The metabolite-containing supernatants were sent for non-targeted metabolic profiling to the Metabolomics Core Facility of Feinberg School of Medicine at Northwestern University (Chicago, IL). Peak areas of metabolites were measured by LC-MS / MS and normalized by dividing by total ion count. Data were analyzed by the MetaboAnalyst V5.0 platform.

[0097] As for flux metabolomics, WT young (3mo) vs. old (18mo) mouse T-cells were activated for 3 days in the presence of lOOIUB / ml IL-2 in wells coated with anti-CD3 (2pg / ml) and anti-CD28 (5pg / ml), then labeled with13C3-pyruvate or13Cs-glutamine for the final hour of activation.13Cs- pyruvate was prepared at a concentration of HOmg / 1 in DMEM pyruvate-free medium.13Cs- glutamine was prepared at a concentration of 584mg / l in a DMEM glutamine-free medium. Metabolites were isolated using cold methanol extraction. Normalized peak areas of13C-labeled metabolites were measured by targeted LC-MS / MS: m + n = mass of the metabolite + n, where n represents the number of heavy carbons (13C). Each isotopologue (m + n) reflects the newly synthesized metabolite generated from the metabolization of the tracer or another metabolite derived from the tracer. The data are presented as the mean ± SD.

[0098] RNA extraction and NanoString nCounter analysis

[0099] Activated T-cell RNA was isolated using RNeasy (Qiagen) and then submitted for NanoString nCounter analysis using the Mouse Metabolic Pathways panel. Samples were run by the Translational Science Laboratory core at MUSC per the manufacturer’s instructions. In short, RNA samples isolated from T-cells were all adjusted to a concentration of 20 ng per pL in nuclease-free water (Fisher Bioreagents, Waltham, MA) for nCounter analysis (nCounter Pro MAX / Flex). Briefly, nCounter analysis begins with the hybridization of 100 ng of RNA to capture and report CodeSet overnight. The Prep Station automatically processes the samples (NanoString, Seattle, WA). The cartridge containing the probes bound to the immobilized RNA is then scanned at 555 fields of view (FOV) into the Digital Analyzer (NanoString) for image acquisition, and barcodes are counted and analyzed through the nCounter analysis software (nSolver 4.0). The gene expression analysis is done using the Mouse Metabolism Panel CodeSet (NanoString), which includes 773 murine genes plus 12 internal reference genes. These 773 murine genes are involved in host susceptibility, the interferon pathway, the innate and adaptive immune response, and homeostasis. Count data generated by NanoString nSolver 4.0 software was analyzed with the DESeq2 package in R (version 4.3.0). Differential gene expression analyses were done with the following contrasts: Old versus Young, AD versus Old, and Old + Fumarate versus Old. DGEs that have absolute logFC bigger than 2 and p-value smaller than 0.05 were considered significant in each contrast. The expected significant genes were used to generate a heatmap using the ComplexHeatmap package in R.

[0100] Quantitative PCR

[0101] Total RNA isolation was performed using RNeasy (Qiagen), and 500ng of total RNA was used for complementary DNA (cDNA) synthesis using the i Script cDNA Synthesis Kit (Bio-Rad). Primers for different RNAs of interest (IL2, IL4, IL17A, IFNy) were prepared, and qPCR was performed using SYBR green Real-Time PCR mix (BioRad). All qPCR primers were synthesized by Integrated DNA Technology (Iowa, USA). The specific qPCR primers designed are listed in the key resources table.

[0102] RNA-seq experiments and analyses

[0103] Total RNA was isolated using RNeasy (Qiagen) and processed per the manufacturer’ s instructions. Sample quality control, RNA library preparation (standard Illumina protocols), and RNA-seq analysis were carried out by the Translational Science Laboratory Core at MUSC using Partek Flow Bioinformatic Software. In short, after the pre-alignment quality check, RNA-seq reads were aligned using the STAR aligner, and the aligned reads were then quantified to mmlO - Ensembl Transcripts release 102. Differential gene expression analyses were performed with the following contrasts: Old versus Young, Old versus Old + Fumarate, and Old + Fumarate versus Young. DGEs with an absolute fold change greater than 1.5 and a p-value smaller than 0,05 were considered significant in each contrast. The expected significant genes were generated using the Metaboanalyst 5.0 software to create a heatmap. Pathway enrichment analysis was performed using the significantly changing DGEs and the KEGG database, and the pathways with the top enrichment scores and p-values of less than 0.05 were displayed. Detection of fumarate levels in serum

[0104] A Fumarate Assay Kit was obtained from Abeam to measure fumarate levels in mouse serum. The manufacturer’s protocol was followed. Briefly, and serum was collected from WT vs. ASLKO mice by submandibular blood collection and centrifugation to separate serum from the rest of the blood. The serum was then diluted 25x and used in the assay to determine fumarate levels using a standard curve.

[0105] IFNy detection by ELISA

[0106] ELISA MAX™ Standard Set Human IFN-y (Biolegend) was used per the manufacturer’s protocol. Pierce™ 96-Well Polystyrene Plate (Thermo Fisher Scientific, cat# 15042) was coated with capture antibody diluted at 1:200 in Coating Buffer and incubated for 24 h at 4°C. Blocking was done for 1 hour at room temperature in Assay Diluent. T-cell supernatants and prepared standards were added to the plate and left incubating at room temperature for 2 hours. After washing, the detection antibody was diluted 1 :200 and then added for 1 hour, after which the plate was washed, and Avidin-HRP solution was added for 30 minutes. Finally, TMB Substrate Solution was added to the plate in the dark, and color change was monitored for changes from blue to yellow. Absorbance was read by a fluorescent plate reader at 450 nm within 15 min.

[0107] MitoTransfer

[0108] Mitochondrial transfer was performed by optimizing a previously published protocol for T-cell applications94. In brief, mitochondria were isolated from the donor T-cells, as described in another section. Recipient T-cells were isolated from the 12-month-old mice, and they were cultured in a 96-well plate and allowed to rest for 2 hours at 37°c in 5% CO2. After 2 hours, mitochondria isolated from an equal number of cells were resuspended in IMDM and added to the recipient T- cells. Cells were centrifuged at 1500xg for 15 minutes at 4°c, then returned to rest at 37°c in 5% CO2 for 2 hours. After the 2-hour rest period, the cells were centrifuged again at 1500xg for 15 min at 4°c. The T-cells were activated as described above for different downstream applications.

[0109] Multiplex Staining + Scanning Optimized multiplex immunofluorescence was performed using the OPAL™ multiplexing method. OPAL™ is based on Tyramide Signal Amplification (TSA) using the Roche Ventana Discovery Ultra Automated Research Stainer (Roche Diagnostics, Indianapolis, IN). Tissues were stained with antibodies against CD3, CD8, and FoxP3, and the fluorescence signals were generated using the different OPAL fluorophores: OPAL dyes 620, 520, and 480 (Akoya Biosciences, Marlborough, MA). Multiplex-stained slides were imaged at 20X magnification using the PhenoImager HT™ Automated Quantitative Pathology Imaging System (Akoya Biosciences, Marlborough, MA) and analyzed using inForm® Tissue Analysis Software (v[2.6.0], Akoya Biosciences, Marlborough, MA). Spatial analysis was performed using the PhenoptrReports Open Source R Package (https: / / akoyabio.github.io / phenoptrReports / index.html, Akoya Biosciences, Marlborough, MA).

[0110] Immunohistochemistry

[0111] Immunohistochemistry was performed on resected tumor samples fixed in formalin by embedding with paraffin and sectioning the paraffin block (5 um slices). Embedding, sectioning, and Ki67 proliferation, the MUSC Histology and Immunohistochemistry Shared Resource staining was done. Ki67 signal was quantified using Image!

[0112] Human cancer tissues and PBMCs

[0113] Human Peripheral Blood Mononuclear Cells (PBMCs) were obtained from STEMCELL Technologies, and they were isolated from healthy, non-smoker female donors of different ages (22yo, 65yo). Tumor tissues and PBMCs from AD versus cognitively healthy patients were obtained from the Cancer Registry and Tissue Biorepository at the Medical University of South Carolina. Donor charts were surveyed to identify donors who had been diagnosed with Alzheimer’s disease and those who hadn’t. Frozen slide sections from tissues from age-, sex-, cancer type-, and race-matched individuals were obtained and analyzed.

[0114] Correlation between AD and cancer diagnosis The MEPS is a nationally representative survey of the United States civilian noninstitutionalized population, medical providers, and employers95. The survey is administered by trained interviewers using a computer-assisted personal interview to collect data on health services utilization, cost of health services, health care financing, and health insurance. The MEPS medical conditions files were analyzed using the International Classification of Diseases (ICD) code G30 to identify AD cases. Non-AD controls were adults with no reported diagnosis of AD. The demographic information of cases and controls was available in the population characteristics data files and is presented in Figure S1A. Similar to AD, cancer diagnosis was ascertained from the medical conditions file using ICD codes (Figure SIB). To minimize confounding bias, AD cases and non-AD controls were matched 1 :1 on age, sex, and race / ethnicity using propensity score matching96.

[0115] Statistical Analyses

[0116] Data were reported as mean ± standard deviation of at least three independent studies (n>3). Group compari sons were performed with either two-tailed unpaired t-tests (and nonparametric tests) or a one-way ANOVA with post-hoc Tukey test for multiple comparisons (and nonparametric or mixed) as appropriate, using Graph Pad Prism. Due to relatively smaller sample sizes in animal studies, the Kruskal-Wallis test was used to compare continuous outcomes among three groups. Because a significant result was discovered, all possible pairwise comparisons were performed using the Wilcoxon rank sum test. P <0.05 was considered significant. The survey design-adjusted Wald F test (for comparison of cancer prevalence), and a logistic regression model (for odds ratio estimation) were used for the cross-sectional MEPS analyses. The inventors used SAS PROC SURVEY procedures for all MEPS data analyses to account for strata, clusters, and weights per MEPS analytical guidelines; significance was tested for 2 -tailed P<0.05.

[0117] RESULTS

[0118] Ancillary epidemiological data on cancer prevalence among patients diagnosed with AD

[0119] Data was used from the Medical Expenditure Panel Survey (MEPS) 2016-2019 and 2021 cycles, a nationally representative survey of non-institutionalized American adults, to examine the odds of cancer diagnosis among adults >60 years based on AD diagnosis. The prevalence and odds of cancer diagnosis in non-AD controls (n=143) were compared to propensity score-matched AD cases (n=143). The prevalence of cancer was statistically significantly higher in non-AD controls (4.9%) versus AD cases (0.25%) (P< 0001) (Figure 1A, Figures S1A, B). The findings of the logistic regression model suggest that the odds of cancer diagnosis were higher (Odds Ratio 21.12 (95% confidence interval: 9.01-49.3) for the non-AD controls compared to the AD cases adjusting for age, sex, and race / ethnicity.

[0120] 3xTg AD mice are protected from cancer development and progression via increased antitumor functions of T-cells in vivo

[0121] To validate the protective roles of AD against cancer growth / progression in vivo in an AD mouse model, the inventors used 3xTg mice, which express three mutated transgenes (APP, MAPT, Psenl) under the control of Thyl promoter63. The inventors exposed young Wild Type (WT) (3 mo), old WT (12 mo), or old 3xTg (12 mo) mice to 4-Nitroquinoline 1-oxide (4NQO), a carcinogen added to drinking water to induce oral squamous cell carcinomas (OSCC) (Figure IB, Figures SIC, D). The negative association between AD and cancer was apparent in this model, as none of the 3xTg mice developed oral tumors (one mouse died from non-cancer-related complications), while all the WT mice, both young and old, developed tumors (Figure IB, Figures SIC, D). Tongues from WT mice showed a significantly higher level of Ki67 staining by immunohistochemistry (IHC) compared to the 3xTg tongues, indicating an increase in cellular proliferation in the WT tongue tumors (Figure SID). Because aging stress induces hyperactive lethal mitophagy in T-cells that inhibit their anti-tumor functions26, the inventors then measured mitophagy in T-cells accumulated in the OSCC tumor tissues by co-staining for LC3-Tom40 in CD3+ tumor-infiltrating T-cells. As shown in Figure 1C, LC3-Tom40 colocalization was decreased in the 3xTg tongues compared to WT controls, indicating a lower level of mitophagy in these 3xTg T-cells than in WT tumor-infiltrating T-cells. The 3xTg tongues were also protected against Treg (FoxP3+ CD4+ T-cells) infiltration as revealed by multiplex staining (Figure S1E, Figure IE), thereby fostering a more aggressive anti-tumor environment in these 3xTg tongues. The CD8+ T-cell infiltration to T-reg infiltration ratio (CD8+ T-cells / Foxp3+ T-cells detected by multiplex staining) was also significantly higher in the 3xTg tongues (Figure S1E).

[0122] Besides their protection against carcinogen-induced tumor incidence and mitophagy in tumorinfiltrating T-cells, 12 mo 3xTg mice also exhibited protection against the growth of exogenous, subcutaneously implanted B16 melanoma tumors (Figure IF, Figure S1F). Since T-cells in the 3xTg mice showed reduced mitophagy (Figure 1C), the next question was whether these T-cells played an essential role in protecting the 3xTg mice against tumor development. When the T-cells in the 3xTg mice were depleted using an anti-CD3 antibody (Figure SIG), the protection of these mice against tumor growth was completely abolished (Figure IF). These data support the critical roles of T-cells in protecting AD mice against tumor growth and progression. After isolating the tumor-infiltrating lymphocytes (TILs) from the B 16 tumors in the WT vs 3xTg mice, the inventors found significantly higher levels of IFNy secretion by the 3xTg TILs, as well as lower levels of FoxP3+ CD4+ regulatory T-cells (Figure 1G, H), which supports the heightened anti-tumor function of the T-cells in the 12 mo 3xTg compared to WT mice. The 3xTg TILs also demonstrated lower levels of mitophagy than WT TILs, as demonstrated by the proximity ligation assay (PLA) measuring LC3-Tom40 interaction specifically in the CD3+ T-cells in the tumors (Figure II).

[0123] APP is one of the transgenes expressed by the 3xTg mouse model, and it is expressed in T-cells58'60. It is directly involved in the inhibition of mitophagy61>62, which was also seen in the tumorinfiltrating lymphocytes in both in vivo tumor models in Figure 1. Notably, the 3xTg AD model uses the Thy 1 promoter to control APP expression, which is activated in both neurons and T-cells63’64. Interestingly, when another AD mouse model, the APP -PSI model, was compared to age- matched WT control mice (12 mo), they were not protected against tumor growth (Figure 1J). Unlike the 3xTg mice, the APP transgene in the APP -PSI mouse model is controlled by the prion protein (PrP) promoter65, which is exclusively expressed in the neurons but not in T-cells of the APP -PSI mice (Figure 1 J, right panel). This raises the question of whether APP might be playing a role in protecting 3xTg T-cells against aging-dependent mitophagy and potentiating their antitumor function, which would explain their superior capacity to secrete IFNy compared to T-cells isolated from 12 mo APP-PS1 mice (Figure SIH). Thus, these data reveal that 3xTg AD mice are protected from tumor growth / progression by increased anti-tumor functions of T-cells, concomitant with inhibition of aging-stress mediated mitophagy in T-cells. The potential role of APP in this phenomenon will be further dissected next.

[0124] APP accumulation in aging AD mouse T-cell mitochondria drives their inflammation

[0125] To better characterize T-cells from WT versus 3xTg AD mice, the inventors examined T-cell survival and measured functional markers in aging WT and AD mouse T-cells. The inventrors isolated CD4+ and CD8+ T-cells from age-matched 10-12-month-old aging WT or 3xTg mice. The inventors used T-cells from 2-3-month-old (mo) mice as controls to measure the effects of aging on T-cell function. While the viability of T-cells from 12 mo AD mice was comparable to that of the age-matched WT T-cells (Figure 2A), 3xTg T-cells (12 mo) were protected against the age-induced decline in IFNy cytokine secretion in both the CD4+ and CD8+ populations compared to age-matched WT T-cells. 12 mo 3xTg T-cells also secreted lower levels of the antiinflammatory cytokine, IL- 10, upon TCR stimulation via plate-bound CD3- and CD28 antibodies compared to 12 mo WT T-cells (Figure 2B, C). To characterize the impact of this phenotype on T-cell anti-tumor function, the inventors performed a polyclonal tumor-killing assay in which T- cells from age-matched WT vs. 3xTg mice (12 mo) were activated by antigens present in the supernatants of MOC2 head and neck tumor cells in culture, before being co-cultured with the MOC2 cells for 24 hours to measure tumor killing. 3xTg T-cells demonstrated a significantly heightened capacity to kill M0C2 tumor cells in culture (Figure 2D), consistent with the elevated levels of IFNy secreted by these cells. Overall, these data highlight the inflammatory advantage of 12 mo 3xTg T-cells, as well as their increased anti-tumor function compared to WT aging T-cells that have reduced anti -tumor functions compared to younger T-cells isolated from 2-3 mo mice, as previously reported26. These data also agree with the in vivo data (Figure 1, Figure SI), which demonstrated the T-cell-mediated protection of 3xTg against tumor growth.

[0126] Increased accumulation of APP and its processed peptides in the mitochondria of AD neurons and its effects on mitochondrial dynamics and mitophagy have been well documented47’51’53’54. Given the intimate relationship between elevated mitophagy and aging-stress-induced decline in T-cell anti-tumor function26, the inventors measured APP accumulation in the T-cells of 3xTg mice (12 mo). Interestingly, 3xTg T-cells showed a significant elevation of APP levels, especially in their mitochondria, as demonstrated by various assays (Figures 2E-H). 3xTg T-cells exhibited a substantial increase in APP levels in their total lysates (Figure 2E). Subcellular fractionation revealed that the increased APP mainly accumulates in the T-cells' mitochondrial fractions (Figure 2F). Immunofluorescence (IF) and proximity ligation assay (PLA) experiments demonstrated the colocalization of APP with the mitochondrial outer-membrane protein Tom20 (Figures 2G, H), further validating the accumulation of APP in the mitochondria. These data indicate that APP mitochondrial accumulation and processing might prevent aging-stress-mediated mitophagy in T- cells, leading to improved anti-tumor T-cell functions.

[0127] Aging 3xTg T-cells are protected against aging-stress mediated, and ceramide-dependent hyperactivated lethal mitophagy

[0128] To determine whether the levels of mitophagy were impacted in the aging 3xTg mice T-cells upon in vitro activation, the inventors measured mitophagy using a mitophagosome-specific dye (Mtphagy) that is only fluorescent when the acidic lysosomes engulf the mitochondria. While 12 mo WT T-cells demonstrated the expected increase in mitophagy upon activation compared to younger T-cells (isolated from 3 mo WT mice), 12 mo 3xTg T-cells were significantly protected from mitophagy compared to 12 mo WT T-cells (Figure 3A). This was consistent with decreased colocalization of the autophagy protein LC3 and the mitochondrial protein Tom20 in T-cells isolated from 12 mo 3xTg compared to WT T-cell counterparts (Figure 3B). Ceramide-dependent mitophagy has explicitly been implicated in the aging stress observed in T-cells26, where Ceramide Synthase 6 (CerS6) is recruited to the mitochondrial membranes to mainly generate C14- and C16- ceramides, which recruit LC3 -containing autophagosomes to mitochondria and induce mitophagy process26. 12 mo 3xTg T-cells were protected against mitochondrial localization of CerS6 (Figure 3C, D), and, in parallel, the aging-induced increase in mitochondrial Cl 4- and Cl 6- ceramide accumulation, measured by lipidomics, was significantly blunted in the 12mo 3xTg compared to WT T-cells (Figure 3E, Figure S2A). Immunofluorescence confirmed the reduction in ceramide accumulation in mitochondria isolated from 12 mo 3xTg compared to WT T-cells (Figure 3F). To delineate the specific role of CerS6 in the observed ceramide-dependent mitophagy and the resultant decrease in T-cell function, the inventors compared the mitophagy levels and function of T-cells from young (3 mo) WT versus Cers6' / _mice upon mimicking aging stress by exposure to sodium selenite (SoSe), which is known to induce ceramide-dependent mitophagy34’66, phenocopying the increase in ceramide-dependent mitophagy observed in aging T-cells26. As expected, CerS6" T-cells were relatively protected against mitophagy compared to their WT counterparts, and their secretion of IFNy was also significantly higher than the WT T-cells, emphasizing the role of CerS6-mediated mitophagy in the decrease in T-cell function with aging stress (Figures S2B-C).

[0129] To define the role of APP in ceramide-dependent mitophagy inhibition, aging stress was mimicked in young WT T-cells (isolated from 3 mo WT mice) using sodium selenite (Na2SeOs, SoSe) treatment in the presence / absence of APP overexpression (Figures S2D-F). The data showed that ectopic expression of APP (APP OE) protected WT T-cells from SoSe-induced mitophagy and increased IFNy secretion compared to their empty vector (EV)-transfected controls (Figures S2E, F). To demonstrate the importance of APP localization to the mitochondria in this inhibition of mitophagy, the inventors generated a mutant APP that does not localize to the mitochondria by deleting the mitochondrial targeting domain (residues 40-51)67. The inventors then compared the protection against mitophagy in Jurkat cells expressing either WT-APP or the mutant (Mut)-APP, which showed significantly less localization to the mitochondria of the Jurkat cells than the WT- APP (Figure 3G, H, K). The results showed superior protection against ceramide-dependent mitophagy in the cells expressing WT-APP compared to the Mut-APP counterparts (Figure 3I-K). These data suggest that the overexpression of APP inhibits aging-mediated mitophagy by localizing to the mitochondria and preventing mitochondrial CerS6 and C14 / C16-ceramide accumulation in 3xTg T-cells, improving their anti-tumor immunity response, like the secretion of crucial effector anti-tumor cytokines such as IFNy. APP prevents mitochondrial trafficking of CerS6 to inhibit ceramide-mediated lethal mitophagy in aging T-cells

[0130] The increase in ceramide species as a response to aging stress has been well-described68’69. However, the shuttling of ceramide synthase enzymes to the mitochondrial membranes has only been characterized in specific contexts. Ceramide-dependent mitophagy in cancer cells and neurons is driven by the pl7 / PERMIT-dependent transport of ceramide synthase 1 (CerSl) to the mitochondria, but pl7 / PERMIT was shown to specifically transport CerSl, and not other ceramide synthases34’66. To better understand the localization / trafficking of CerS6 to the mitochondria in aging T-cells, the inventors co-immunoprecipitated CerS6 in old versus young T-cells (isolated from 12 vs. 3 mo WT mice) and identified proteins that were explicitly interacting with CerS6 in the aging T-cells but not the young ones by proteomics (Figure 3L). Among the identified proteins, only ATAD3 was confirmed to interact with CerS6 in aging T-cells by co-immunoprecipitation (co-IP) and proximity ligation assay (PLA) experiments (Figure 3L-M). Interestingly, 12 mo 3xTg T-cells were significantly protected from the interaction between CerS6 and ATAD3 (Figure 3M), which is consistent with the decrease in mitochondrial CerS6 and C14- / C16-ceramide accumulation in 12 mo 3xTg T-cells compared to WT T-cells (Figure 3C-E). SiRNA-mediated knockdown of ATAD3 in 3 mo WT T-cells (Figure S2G) also attenuated ceramide-dependent mitophagy upon treatment with SoSe. This was demonstrated by the significantly reduced Mtphagy dye fluorescence (Figure 3N), protection against CerS6 and ceramide accumulation in the mitochondria (Figures S2H-I), and enhanced IFNy secretion compared to Scr-siRNA- transfected WT T-cell counterparts (Figure 30). ATAD3 is prominent in regulating the endoplasmic reticulum (ER) interaction with the mitochondria in cells70. Thus, the inventors hypothesized that AT AD3 -mediated trafficking of CerS6 from the ER to the mitochondria might be regulated by inducing ER-mitochondria membrane association / contacts. siRNA-mediated ATAD3 knockdown, or overexpressing APP, reduced the number of ER-mitochondria contact sites upon inducing mitophagy by SoSe, as measured by PDI-Tom40 colocalization (Figures S2J- K). These data reveal a new role of ATAD3 in inducing mitochondrial trafficking of CerS6 in aging T-cells by enhanced ER-mitochondrial membrane associations to mediate hyperactivated mitophagy, which APP prevents in AD T-cells. A04O, but not Ap42, contributes to mitophagy inhibition in aging 3xTg T-cells

[0131] The inventors next examined the roles of the APP-derived P-amyloid peptides A|34O and Ap4271'73in regulating aging-stress-mediated mitophagy in T-cells71'73. The data showed that only AP40, not Ap42, interacts with mitochondrial Tom20 in 12 mo 3xTg T-cells (Figures S3A, B). Also, treating 12 mo WT T-cells with exogenous Ap40 peptide decreased mitophagy and mitochondrial ceramide accumulation. In contrast, exogenous Ap42 peptide had no effects on mitophagy or mitochondrial ceramide levels compared to Scr-peptide treated controls (Figures S3C, D). Just like endogenous Ap40 in the 3xTg T-cells, exogenous Ap40 also localized to the mitochondria as demonstrated by a PLA that shows colocalization between Ap40 and Tom40 upon the addition of exogenous AP40 to old WT T-cells (Figures S3E). The localization of AP40 to the mitochondria likely plays a role in inhibiting mitophagy in the treated T-cells. These data are consistent with the induction of activation markers CD69 and CD25 and increased secretion of IFNy while reducing anti-inflammatory cytokine IL-10 in 12 mo WT T-cells in response to exogenous Ap40, but not Ap42 (Figures S3F, G). As for tumor-killing potential, Ap40 significantly increased the tumorkilling potential of 12 mo Pmel T-cells, which have a transgene specifically targeting B16 melanoma cells, while Ap42 did not induce a similar enhancement of tumor-killing (Figures S3H). To test if the processing of APP to Ap40 was essential for the inhibition of aging-mediated stress, the inventors treated 12 mo 3xTg T-cells with increasing concentrations of a y-secretase inhibitor (DAPT) or a P-secretase inhibitor (LY2886721), which alter the processing of APP into its subproducts such as AP40, AP42, and other APP C-terminal fragments. The inhibition of y- secretase cleaves the APP protein downstream to the Ap40 domain and did not impact IFNy secretion (Figure S3I). On the other hand, inhibition of P-secretase, which prevents the processing of APP into a C-terminal fragment including the Ap40 peptide, decreased IFNy secretion in 12 mo 3xTg T-cells compared to untreated controls (Figure S3J). These data suggest that the processing of APP into AP40 by P-secretase plays a crucial role in protecting aging-stress-mediated mitophagy in AD T-cells. APP protects aging AD T-cells from mitophagy-mediated metabolic defects, including fumarate depletion

[0132] Given the central role of mitochondria in cellular metabolism, the inventors next examined the hydrophilic metabolome of old versus young T-cells via LC-MS / MS metabolomics. Aging T-cells isolated from 12 mo WT mice demonstrated a significant decrease in several mitochondrial metabolites involved in the tricarboxylic acid (TCA) cycle, namely fumarate, malate, and argininosuccinate, compared to their younger counterparts (isolated from 3 mo WT mice) (Fig. 4A). These data are consistent with the recent data which showed fumarate depletion as a metabolic signature of ceramide-mediated mitophagy in neurons66. Metabolic flux experiments using CIS- labeled pyruvate or glutamine showed similar results, with the levels of fumarate and malate both significantly reduced in the aging T-cells compared to their younger controls, isolated from 12 versus 3 mo WT mice (Figure S4). Aging AD T-cells isolated from 12 mo 3xTg mice were protected from this metabolic defect, and fumarate, malate, and argininosuccinate levels were preserved, comparable to those detected in younger T-cells (Figure 4B).

[0133] To determine the effects of fumarate on aging-mediated mitophagy in T-cells, the inventors performed in vitro reconstitution experiments. Exogenous fumarate supplementation in aging WT T-cells (isolated from 12 mo WT mice) inhibited mitophagy (Figure 5A-D) as demonstrated by decreased Mtphagy dye fluorescence (Figure 5A), as well as the preservation of mitochondrial proteins AC02, Tom40, and Tim23 compared to vehicle-treated old T-cells (Figure 5B-D). Exogenous fumarate supplementation also increased CD8+ T-cell IFNy secretion compared to vehicle-treated control T-cells (Figure 5E). Then, to test the effects of exogenous fumarate in vivo, 24 mo WT mice were treated with fumarate for 2 months before their spleen-derived T-cells were collected and activated. Interestingly, the in vivo treatment of 24 mo mice with exogenous fumarate was sufficient to decrease mitophagy (Figure S5A) and improve activated T-cell viability, activation, and secretion of anti-tumor cytokines IFNy or Granzyme-B (GZB) (Figures 5F-I). Activated T-cells isolated from the fumarate-treated 24-month-old mice also secreted less IL-10, which is anti-inflammatory, demonstrating the roles of fumarate in restoring inflammatory potential of aging T-cells (Figure 5 J). Further, data showed that exogenous fumarate enhanced the tumor-killing function of aging T-cells, as demonstrated by the polyclonal tumor-killing assay with B16-melanoma cells (Figure 5K). Given the published impact of fumarate on mitophagy in mouse brains66, the inventors performed different behavioral assays to ascertain that the treatment was not leading to neurological and cognitive deficits in the mice. The old mice treated with vehicle and those treated with fumarate performed similarly in the Rotarod and Novelty Y-Maze tests (Figure S5B). To define the role of fumarate in protecting against ceramide-dependent mitophagy, the inventors isolated T-cells from Argininosuccinate Lyase (ASL) knock-out mice (ASLKO). The inventors exposed the T-cells to SoSe to induce mitophagy. The absence of ASL in these mice leads to significantly lower fumarate levels systemically (Figure S5C). As expected, ASLKO T- cells underwent significantly elevated levels of mitophagy upon SoSe exposure compared to their WT counterparts (Figure 5L), confirming the critical role of fumarate in protecting against excessive mitophagy.

[0134] RNA sequencing of the aging T-cells collected from fumarate-treated mice showed an impressive reversal of the transcriptional profile of the untreated aging T-cells, closely mimicking their younger T-cell counterparts after the 2-month fumarate treatment period (Figure S5D). An analysis of the pathway changes showed that several metabolic pathways were significantly enriched within the genes decreasing in aging T-cells but recovering upon fumarate treatment (Figure S5E), indicating the central role of fumarate in regulating both aging T-cell mitophagy and metabolism. The top pathways significantly increasing in the old T-cells but inhibited by fumarate were diverse, with no apparent patterns emerging (Figure S5F).

[0135] Using the NanoString nCounter® technology to detect transcriptional changes in metabolic genes specifically, the inventors identified a list of genes that were significantly restored in fumarate- treated aging T-cells to the levels detected in their younger counterparts compared to vehicle- treated controls (Figure 5M). One of the interesting genes that increased with age but then attenuated in response to fumarate treatment was Foxp3, a marker of regulatory T-cells (T-regs) that play a crucial role in tumor tolerance and progression. Upon comparing the transcriptional profiles of old WT T-cells to either fumarate-treated WT T-cells or age-matched 3xTg T-cells, the inventors identified a list of genes that were similarly impacted by the addition of fumarate and by the aging AD T-cell phenotype (Figure 5N), pointing to a mechanistic role of elevated fumarate levels in maintaining healthy T-cell function and restoring an epigenetic / transcriptional phenotype in AD T-cells that mimics younger WT T-cells. The inventors confirmed the protection against T- reg induction upon fumarate treatment or in AD T-cells by flow cytometry, which showed a significant decrease in both percent positivity as well as the mean fluorescence intensity (MFI) of Foxp3 in CD4+ T-cells (Figure 50, P). This indicates a decrease in both the number of Tregs as well as the expression of Foxp3 in the AD and fumarate-treated T-cells. This is also consistent with the decrease in tumor-infiltrating Tregs observed in both the 4NQ0 tumor model as well as the B 16 melanoma tumor model shown in Figure 1 (Figure IE, H). In Figure 5N, highlighted in red boxes are the genes that significantly changed with aging but were restored in both the AD T- cells and upon addition of fumarate. Besides Foxp3, among the genes that were restored to young expression levels upon fumarate treatment or in the aging AD T-cells were Gadl (glutamate decarboxylase 1), Scdl (Stearoyl-coA desaturase 1), and Hsdl lbl (hydroxy steroid 11-beta dehydrogenase 1), which encode proteins that regulate amino acid and lipid metabolism. These data suggest that 3xTg AD T-cells are protected from aging-stress-mediated mitophagy and related fumarate depletion, as well as defects in amino acid and lipid metabolism compared to WT T-cells.

[0136] Succination is a post-translational modification that results from increased levels of fumarate74. This chemical modification of proteins at the level of cysteine residues has been shown to regulate protein function74. One of the proteins with a catalytic cysteine that is heavily involved in ceramide-dependent mitophagy is Parkin (PRKN)34>75. Given the clear role of fumarate in impacting aging T-cell ceramide-dependent mitophagy, metabolism, and function, the inventors next asked whether succination of Parkin at its catalytic cysteine C431 might be mediating the effect of fumarate on T-cell mitophagy. Using an antibody against succinated cysteine (S-(2- succinyl)cysteine (2SC)), the inventors found that Parkin succination significantly decreased in old T-cells, but was restored in the 3xTg T-cells or upon treating with fumarate (Figure 5Q). This reflected the increase in mitophagy in the old T-cells, and its suppression in the 3xTg or fumarate- treated old T-cells. To further dissect the role of Parkin succination in this fumarate-mediated inhibition of ceramide-dependent mitophagy, the inventors overexpressed WT-Parkin or a mutated Parkin with C431D mutation which mimics succination at C431, therefore mimicking a high fumarate level state (Figure S5G). While the overexpression of WT-Parkin increased the level of mitophagy (Figure 5R) and decreased the secretion of IFNy in WT T-cells (Figure 5S), the cells transfected with C431D mutant Parkin were significantly protected against this effect. The level of Parkin recruitment to the mitochondria was also significantly lower in the cells transfected with mutated C43 ID Parkin compared to WT-Parkin (Figure S5H), emphasizing the role of succination in inhibiting Parkin function. This further delineated the mechanism by which fumarate controls ceramide-dependent mitophagy in aging T-cells, maintaining their anti-tumor inflammation.

[0137] APP expression or fumarate supplementation improves the effectiveness of adoptive T-cell transfer in controlling tumor growth / progression

[0138] To delineate the functional advantage of aging-stress-mediated mitophagy inhibition in T-cells by APP expression or fumarate supplementation, the inventors performed adoptive cell transfer (ACT) experiments. To achieve this, the inventors cross-bred Pmel with 3xTg mice to obtain 3xTg-Pmel mice (Figure 6A, Figure S6A) that express a TCR transgene (Tg) specific to melanoma-associated antigen (gp-100), which allows them to target and kill B16 melanoma cells specifically. Increased expression of the APP protein, specifically in the T-cells, was then measured by Western blotting, which demonstrated an increased level of APP exclusively in the 3xTg-Pmel T-cells (Figure 6B). APP " T-cells were used as a negative control. Genotyping of all the mice demonstrated the presence of the Pmel Tg in the 3xTg-Pmel and the Ctrl-Pmel mice, indicating that both groups have T-cells with TCRs that specifically target B 16-melanoma tumors. T-cells from young (3 mo) versus old (12 mo) Ctrl-Pmel mice, as well as T-cells from old (12 mo) 3xTg mice, were then activated by gplOO (melanocyte-specific antigen) for 3 days in culture (Figure S6A) then injected into the recipient mice, whose T-cells were depleted, with subcutaneously established melanoma tumors. As seen in Figure 6C, D, old Ctrl-Pmel T-cells failed to control tumor growth, while old 3xTg-Pmel T-cells were just as successful as the young T-cells in controlling tumor growth (Figure 6C, D). Treating the recipient mice with fumarate restored the function of the transferred old WT T-cells, enabling them to control tumor growth in all but one animal (Figure 6C, D). The TILs from the mice injected with 3xTg-Pmel T-cells, as well as those that were treated with fumarate, demonstrated superior function as shown by increased levels of IFNy and GZB secretion and inhibition of mitophagy compared to WT and vehicle-treated T-cells (Figure 6E-G). Also, CD3+ and CD8+ T-cell infiltration into the tumor microenvironment was increased upon using T-cells from 3xTg mice or treating with fumarate (Figures S6B, C). Thus, these results demonstrate the potential of restoring the anti -tumor function of aged T-cells used in adoptive cell transfer studies by expressing the APP transgene in T-cells or increasing the fumarate levels to improve their anti-tumor functions.

[0139] Transfer of mitochondria from AD T-cells to aging WT T-cells improves their anti-tumor function

[0140] With the essential role of mitochondrial dynamics in determining the anti-tumor function of aging T-cells now evident, the inventors transferred mitochondria (MitoTransfer) isolated from 3xTg T- cells into aging WT T-cells (Supp. Fig S6D). To verify the effectiveness of the MitoTransfer, the inventors first stained the donor 3xTg T-cells with MitoTracker Red (MTR), which specifically labels their mitochondria (Figure S6D). After the completion of the MitoTransfer, the fluorescence of MTR in the recipient T-cells was assessed, revealing a significantly increased level of MTR fluorescence, indicating that the MitoTransfer was successful and that the donor 3xTg mitochondria are now in the aging recipient WT T-cells (Figure 6H). The transferred mitochondria maintained their AD phenotype, as demonstrated by the continued accumulation of APP in these mitochondria after MitoTransfer (Figure 61). These transferred mitochondria were also resistant to CerS6 recruitment and mitophagy induction (Figure 6J, K). To assess the functional impacts of this MitoTransfer, IFNv secretion by the recipient aging WT T-cells was measured by intracellular flow cytometry, which revealed a significant increase in IFNv secretion by the aging T-cells after MitoTransfer of 3xTg mitochondria (Figure 6L). The recipient T-cells with the 3xTg mitochondria also had an elevated tumor-killing potential, as determined by a tumor-killing co-culture assay with B 16 tumor cells (Figure 6M). Recipient cells were implanted with mitochondria from young T-cells as a positive control (Figure 6 J-M). To demonstrate the therapeutic potential of this strategy, the inventors adoptively transferred aging Pmel T-cells into mice bearing melanoma tumors after MitoTransfer of young, old, or 3xTg mitochondria (Figure 6N). The old T-cells with AD MitoTransfer were significantly more successful in inhibiting tumor growth, emphasizing the role of AD mitochondria in protecting against aging-induced decline in anti -turn or T-cell function while also demonstrating longer-term clinical potential of MitoTransfer in cancer therapy.

[0141] Human aging T-cells display similar metabolic and functional changes as mouse T-cells

[0142] To validate that the metabolic changes detected in aging mouse T-cells are due to ceramidedependent mitophagy that resulted in fumarate depletion, the inventors performed metabolomics in human T-cells isolated from 22 vs. 65-year-old (yo) healthy donors. The data showed decreased malate and fumarate levels in human T-cells isolated from 65 yo compared to 22 yo donors (Figure 7A). Both CD4+ and CD8+ human T-cells showed an increase in the levels of mitophagy with age, and the mitophagy in CD8+ T-cells (isolated from 65 yo donor) was reduced upon adding fumarate (Figure 7B, D). As measured by ELISA, T-cells from 65 yo donors also had reduced IFNy secretion (Figure 7C). As expected, the aging human T-cells demonstrated significantly increased LC3-Tom20 interaction, which was prevented by fumarate treatment (Figure 7D). In the 65-year-old T-cells, CerS6 interaction was increased with both Tom20 and ATAD3 (Figure 7E, F), indicating an increase in the AT AD3 -mediated shuttling of the CerS6 to the mitochondria to induce ceramide-dependent hyperactivated mitophagy, which was almost completely abolished by the addition of fumarate (Figure 7E, F).

[0143] Next, the inventors measured the levels of APP in peripheral blood mononuclear cells (PBMCs) isolated from age-matched old donors (60-80 years old) and designated them APP-high or APP- low (Figure S7A) to measure the effect of APP on human T-cell mitophagy. As expected, the APP- high T-cells exhibited less mitophagy compared to the APP -low T-cells, reinforcing the role of APP in mitophagy inhibition (Figure S7B). Finally, blood and tissue samples from AD patients with cancer were compared to age-matched cognitively healthy controls with matched cancers. AD T-cells had increased IFNy RNA expression, as measured by qPCR (Figure S7C). Moreover, the inventors obtained tumor tissues from cancer patients who had AD or not and examined their TILs. The TILs in the head and neck cancer tissue of cognitively healthy versus AD patients were stained by anti-CD3, and the colocalization of LC3 and Tom40 was assessed by IF to quantify the extent of mitophagy. Data showed decreased mitophagy in the AD TILs compared to age-matched control cancer patients (Figure S7D). The TILs in the AD patient tumors also had a higher level of APP localization to their mitochondria, as measured by PLA (Figure S7E). The inventors also measured the succination of proteins in these TILs as an indirect measure of fumarate7476, using an anti-succination antibody in CD3+ TILs in head and neck cancer tissue from AD versus age- matched cognitively healthy controls. Data revealed an increased level of succination in the AD TILs compared to their control counterparts (Figure S7F), indicating increased fumarate in the AD TILs compared to controls. These data demonstrate that human T-cells isolated from AD patients exhibit protection from aging-mediated mitophagy like those observed in the 3xTg mouse model. These data are also consistent with increased APP in mitochondria of AD T-cells, which decreases mitophagy and increases anti-tumor cytokine secretion, like IFNy. This is accompanied by elevated levels of fumarate, which in turn support the reduction in mitophagy and the increase in human AD T-cell anti-tumor function. These data suggest that T-cells play vital roles in controlling tumor growth / proliferation in AD patients due to inhibition of aging-mediated and ceramidedependent mitophagy with improved fumarate metabolism.

[0144] REFERENCES

[0145] 1. Driver, J. A., Beiser, A., Au, R., Kreger, B.E., Splansky, G.L., Kurth, T., Kiel, D.P., Lu, K.P., Seshadri, S., and Wolf, P.A. (2012). Inverse association between cancer and Alzheimer's disease: results from the Framingham Heart Study. BMJ 344, el442. 10.1136 / bmj.el442.

[0146] 2. Lanni, C., Masi, M., Racchi, M., and Govoni, S. (2021). Cancer and Alzheimer's disease inverse relationship: an age-associated diverging derailment of shared pathways. Mol Psychiatry 26, 280-295. 10.1038 / s41380-020-0760-2.

[0147] 3. Li, J.M., Liu, C., Hu, X., Cai, Y., Ma, C., Luo, X.G., and Yan, X.X. (2014). Inverse correlation between Alzheimer's disease and cancer: implication for a strong impact of regenerative propensity on neurodegeneration? BMC Neurol 14, 211. 10.1186 / sl2883- 014-0211-2.

[0148] 4. Realmuto, S., Cinturino, A., Amao, V., Mazzola, M.A., Cupidi, C., Aridon, P., Ragonese, P., Savettieri, G., and D'Amelio, M. (2012). Tumor diagnosis preceding Alzheimer's disease onset: is there a link between cancer and Alzheimer's disease? J Alzheimers Dis 31, 177-182. 10.3233 / JAD-2012-120184. Rogers, N.K., Romero, C., SanMartin, C.D., Ponce, D.P., Salech, F., Lopez, M.N., Gleisner, A., Tempio, F., and Behrens, M L (2020). Inverse Relationship Between Alzheimer's Disease and Cancer: How Immune Checkpoints Might Explain the Mechanisms Underlying Age-Related Diseases. J Alzheimers Dis 73, 443-454. 10.3233 / J AD-190839. Zablocka, A., Kazana, W., Sochocka, M., Stanczykiewicz, B., Janusz, M., Leszek, J., and Orzechowska, B. (2021). Inverse Correlation Between Alzheimer's Disease and Cancer: Short Overview. Mol Neurobiol 58, 6335-6349. 10.1007 / s 12035-021-02544-1. Musicco, M., Adomi, F., Di Santo, S., Prinelli, F., Pettenati, C., Caltagirone, C., Palmer,

[0149] K., and Russo, A. (2013). Inverse occurrence of cancer and Alzheimer disease: a population-based incidence study. Neurology 81, 322-328.

[0150] 10.1212 / WNL.0b013e31829c5ecl. Roe, C.M., Fitzpatrick, A.L., Xiong, C., Sieh, W. , Kuller, L., Miller, J.P., Williams, M.M., Kopan, R., Behrens, M.I., and Morris, J.C. (2010). Cancer linked to Alzheimer disease but not vascular dementia. Neurology 74, 106-112. 10.1212 / WNL.0b013e3181c91873. Chen, X., and Holtzman, D.M. (2022). Emerging roles of innate and adaptive immunity in Alzheimer's disease. Immunity 55, 2236-2254. 10.1016 / j.immuni.2022.10.016. Gate, D., Saligrama, N., Leventhal, O., Yang, A.C., Unger, M.S., Middeldorp, J., Chen, K., Lehallier, B., Channappa, D., De Los Santos, M.B., et al. (2020). Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer's disease. Nature 577, 399-404. 10.1038 / s41586-019-l 895-7. Xiong, L.L., Xue, L.L., Du, R.L., Niu, R.Z , Chen, L., Chen, L, Hu, Q., Tan, Y.X., Shang, H.F., Liu, J., et al. (2021). Single-cell RNA sequencing reveals B cell-related molecular biomarkers for Alzheimer's disease. Exp Mol Med 53, 1888-1901. 10.1038 / sl2276-021- 00714-8. Sultana, R., Mecocci, P., Mangialasche, F., Cecchetti, R., Baglioni, M., and Butterfield, D.A. (2011). Increased protein and lipid oxidative damage in mitochondria isolated from lymphocytes from patients with Alzheimer's disease: insights into the role of oxidative stress in Alzheimer's disease and initial investigations into a potential biomarker for this dementing disorder. J Alzheimers Dis 24, 77-84. 10.3233 / JAD-2011-101425. Stieler, J.T., Lederer, C., Bruckner, M.K., Wolf, H., Holzer, M., Gertz, H.J., and Arendt, T. (2001). Impairment of mitogenic activation of peripheral blood lymphocytes in Alzheimer's disease. Neuroreport 12, 3969-3972. 10.1097 / 00001756-200112210-00023. St-Amour, I., Bosoi, C.R., Pare, I., Ignatius Arokia Doss, P.M., Rangachari, M., Hebert, S.S., Bazin, R., and Calon, F. (2019). Peripheral adaptive immunity of the triple transgenic mouse model of Alzheimer's disease. J Neuroinflammation 16, 3. 10.1186 / sl2974-018- 1380-5. Bonotis, K., Krikki, E., Holeva, V., Aggouridaki, C., Costa, V., and Baloyannis, S. (2008). Systemic immune aberrations in Alzheimer's disease patients. J Neuroimmunol 193, 183- 187. 10.1016 / j.jneuroim.2007.10.020. Spurred, E.L., and Lockley, M. (2014). Adaptive immunity in cancer immunology and therapeutics. Ecancermedicalscience 8, 441. 10.3332 / ecancer.2014.441. Waldman, A.D., Fritz, J.M., and Lenardo, MJ. (2020). A guide to cancer immunotherapy: from T cell basic science to clinical practice. Nat Rev Immunol 20, 651-668. 10.1038 / s41577-020-0306-5. Zhang, Z., Liu, S., Zhang, B., Qiao, L., Zhang, Y., and Zhang, Y. (2020). T Cell Dysfunction and Exhaustion in Cancer. Front Cell Dev Biol 8, 17. 10.3389 / fcell.2020.00017. Chaudhary, 0., Trotta, D., Wang, K., Wang, X., Chu, X., Bradley, C., Okulicz, J., Maves, R.C., Kronmann, K., Schofield, C.M., et al. (2022). Patients with HIV-associated cancers have evidence of increased T cell dysfunction and exhaustion prior to cancer diagnosis. J Immunother Cancer 10. 10.1136 / jitc-2022-004564. Ott, A., Breteler, M.M., van Harskamp, F., Stijnen, T., and Hofman, A. (1998). Incidence and risk of dementia. The Rotterdam Study. Am J Epidemiol 147, 574-580. 10.1093 / oxfordjournals.aje.a009489. Kaur, A., Webster, M.R., Marchbank, K., Behera, R., Ndoye, A., Kugel, C.H., 3rd, Dang, V.M., Appleton, J., O'Connell, M.P., Cheng, P., et al. (2016). sFRP2 in the aged microenvironment drives melanoma metastasis and therapy resistance. Nature 532, 250- 254. 10.1038 / naturel7392. Kishton, R.J., Sukumar, M., and Restifo, N.P. (2017). Metabolic Regulation of T Cell Longevity and Function in Tumor Immunotherapy. Cell Metab 26, 94-109. 10.1016 / j.cmet.2017.06.016. Le Page, A., Dupuis, G., Larbi, A., Witkowski, J.M., and Fulop, T. (2018). Signal transduction changes in CD4(+) and CD8(+) T cell subpopulations with aging. Exp Gerontol 105, 128-139. 10.1016 / j.exger.2018.01.005. Martinez-Iimenez, C.P., Eling, N., Chen, H.C., Vallejos, C.A., Kolodziejczyk, A.A., Connor, F., Stojic, L., Rayner, T.F., Stubbington, M.J.T., Teichmann, S.A., et al. (2017). Aging increases cell-to-cell transcriptional variability upon immune stimulation. Science 355, 1433-1436. 10.1126 / science.aah4115. Naumov, Y.N., Naumova, E.N., Yassai, M.B., and Gorski, J. (2011). Selective T cell expansion during aging of CD8 memory repertoires to influenza revealed by modeling. J Immunol 186, 6617-6624. 10.4049 / jimmunol.1100091. Vaena, S., Chakraborty, P., Lee, H.G., Janneh, A.H., Kassir, M.F., Beeson, G., Hedley, Z., Yalcinkaya, A., Sofi, M.H., Li, H., et al. (2021). Aging-dependent mitochondrial dysfunction mediated by ceramide signaling inhibits antitumor T cell response. Cell Rep 35, 109076. 10.1016 / j.celrep.2021.109076. Brown-Borg, H.M., and Anderson, R.M. (2017). Metabolic adventures in aging research. Mol Cell Endocrinol 455, 1-3. 10.1016 / j.mce.2017.08.012. Bektas, A., Schurman, S.H., Gonzalez-Freire, M., Dunn, C.A., Singh, A.K., Macian, F., Cuervo, A.M., Sen, R., and Ferrucci, L. (2019). Age-associated changes in human CD4(+) T cells point to mitochondrial dysfunction consequent to impaired autophagy. Aging (Albany NY) 11, 9234-9263. 10.18632 / aging.102438. O'Sullivan, D., van der Windt, G.J.W., Huang, S.C., Curtis, J.D., Chang, C.H., Buck, M.D., Qiu, J., Smith, A.M., Lam, W.Y., DiPlato, L.M., et al. (2018). Memory CD8(+) T Cells Use Cell-Intrinsic Lipolysis to Support the Metabolic Programming Necessary for Development. Immunity 49, 375-376, 10.1016 / j.immuni.2018.07.018. Ogretmen, B. (2018). Sphingolipid metabolism in cancer signalling and therapy. Nat Rev Cancer 18, 33-50. 10.1038 / nrc.2017.96. Pewzner-Jung, Y., Ben-Dor, S., and Futerman, A.H. (2006). When do Lasses (longevity assurance genes) become CerS (ceramide synthases)9: Insights into the regulation of ceramide synthesis. J Biol Chem 281, 25001-25005. 10.1074 / jbc.R600010200. Levy, M., and Futerman, A.H. (2010). Mammalian ceramide synthases. IUBMB Life 62, 347-356. 10.1002 / iub.319. Sentelie, R D., Senkal, C.E., Jiang, W., Ponnusamy, S., Gencer, S., Selvam, S.P., Ramshesh, V.K., Peterson, Y.K., Lemasters, J.J., Szulc, Z.M., et al. (2012). Ceramide targets autophagosomes to mitochondria and induces lethal mitophagy. Nat Chem Biol 8, 831-838. 10.1038 / nchembio. l059. Oleinik, N., Kim, J., Roth, B.M., Selvam, S.P., Gooz, M., Johnson, R.H., Lemasters, J.J., and Ogretmen, B. (2019). Mitochondrial protein import is regulated by pl7 / PERMIT to mediate lipid metabolism and cellular stress. Sci Adv 5, eaaxl978. 10.1126 / sciadv.aaxl978. Karakaya, E., Oleinik, N., Edwards, J., Tomberlin, J., Barker, R.B., Berber, B., Ericsson, M., Alsudani, H., Ergul, A., Beyaz, S., et al. (2024). pl7 / C18-ceramide-mediated mitophagy is an endogenous neuroprotective response in preclinical and clinical brain injury. PNAS Nexus 3, pgae018. 10.1093 / pnasnexus / pgae018. Jetto, C.T., Nambiar, A., and Manjithaya, R. (2022). Mitophagy and Neurodegeneration: Between the Knowns and the Unknowns. Front Cell Dev Biol 10, 837337. 10.3389 / fcell.2022.837337. Zhu, J.H., Guo, F., Shelburne, J., Watkins, S., and Chu, C.T. (2003). Localization of phosphorylated ERK / MAP kinases to mitochondria and autophagosomes in Lewy body diseases. Brain Pathol 13, 473-481. 10.1111 / j .1750-3639.2003 ,tb00478.x. Ge, P., Dawson, V.L., and Dawson, T.M. (2020). PINK1 and Parkin mitochondrial quality control: a source of regional vulnerability in Parkinson's disease. Mol Neurodegener 15, 20. 10.1186 / S13024-020-00367-7. Valente, E.M., Abou-Sleiman, P.M., Caputo, V., Muqit, M.M., Harvey, K., Gispert, S., Ali, Z., Del Turco, D., Bentivoglio, A R., Healy, D.G., et al. (2004). Hereditary early-onset Parkinson's disease caused by mutations in PINK1. Science 304, 1158-1160. 10.1126 / science.1096284. Khalil, B., El Fissi, N., Aouane, A., Cabirol-Pol, M.J., Rival, T., and Lievens, J.C. (2015). PINK 1 -induced mitophagy promotes neuroprotection in Huntington's disease. Cell Death Dis 6, el617. 10.1038 / cddis.2014.581. Martinez -Vicente, M., Talloczy, Z., Wong, E., Tang, G, Koga, H., Kaushik, S., de Vries, R., Arias, E., Harris, S., Sulzer, D., and Cuervo, A.M. (2010). Cargo recognition failure is responsible for inefficient autophagy in Huntington's disease. Nat Neurosci 13, 567-576. 10.1038 / nn.2528. Rogers, R.S., Tungtur, S., Tanaka, T., Nadeau, L.L., Badawi, Y., Wang, H., Ni, H.M., Ding, W.X., and Nishimune, H. (2017). Impaired Mitophagy Plays a Role in Denervation of Neuromuscular Junctions in ALS Mice. Front Neurosci 11, 473. 10.3389 / fnins.2017.00473. Tak, Y.J., Park, J.H., Rhim, H., and Kang, S. (2020). ALS-Related Mutant SOD1 Aggregates Interfere with Mitophagy by Sequestering the Autophagy Receptor Optineurin. Int J Mol Sci 21. 10.3390 / ijms21207525. Oleinik, N., Albayram, 0., Kassir, M.F., Atilgan, F.C., Walton, C., Karakaya, E., Kurtz, J., Alekseyenko, A., Alsudani, H., Sheridan, M., et al. (2023). Alterations of lipid-mediated mitophagy result in aging-dependent sensorimotor defects. Aging Cell 22, el3954. 10.1111 / acel.13954. Chakravorty, A., Jetto, C.T., and Manjithaya, R. (2019). Dysfunctional Mitochondria and Mitophagy as Drivers of Alzheimer's Disease Pathogenesis. Front Aging Neurosci 77, 311. 10.3389 / fnagi.2019.00311. Fang, E.F., Hou, Y., Palikaras, K., Adriaanse, B.A., Kerr, J.S., Yang, B , Lautrup, S., Hasan-Olive, M.M., Caponio, D., Dan, X., et al. (2019). Mitophagy inhibits amyloid-beta and tau pathology and reverses cognitive deficits in models of Alzheimer's disease. Nat Neurosci 22, 401-412. 10.1038 / s41593-018-0332-9. Martin-Maestro, P., Gargini, R., Garcia, E., Simon, D , Avila, J., and Garcia-Escudero, V. (2019). Mitophagy Failure in APP and Tau Overexpression Model of Alzheimer's Disease. J Alzheimers Dis 70, 525-540. 10.3233 / JAD-190086. Ye, X., Sun, X., Starovoytov, V., and Cai, Q. (2015). Parkin-mediated mitophagy in mutant hAPP neurons and Alzheimer's disease patient brains. Hum Mol Genet 24, 2938-2951. 10.1093 / hmg / ddv056. Lee, J.H., Yu, W.H., Kumar, A., Lee, S., Mohan, P.S., Peterhoff, C.M., Wolfe, D.M., Martinez-Vicente, M., Massey, A.C., Sovak, G., et al. (2010). Lysosomal proteolysis and autophagy require presenilin 1 and are disrupted by Alzheimer-related PSI mutations. Cell 141, 1146-1158. 10.1016 / j.cell.2010.05.008. Fedeli, C., Filadi, R., Rossi, A., Mammucari, C., and Pizzo, P. (2019). PSEN2 (presenilin 2) mutants linked to familial Alzheimer disease impair autophagy by altering Ca(2+) homeostasis. Autophagy 75, 2044-2062. 10.1080 / 15548627.2019.1596489. Reddy, P.H., and Beal, M.F. (2008). Amyloid beta, mitochondrial dysfunction and synaptic damage: implications for cognitive decline in aging and Alzheimer's disease. Trends Mol Med 14, 45-53. 10.1016 / j.molmed.2007.12.002. Pradeepkiran, J.A., and Reddy, P.H. (2020). Defective mitophagy in Alzheimer's disease. Ageing Res Rev 64, 101191. 10.1016 / j .arr.2020.101191. Lee, S.E., Kwon, D., Shin, N., Kong, D., Kim, N.G., Kim, H.Y., Kim, M.J., Choi, S.W., and Kang, K.S. (2022). Accumulation of APP-CTF induces mitophagy dysfunction in the iNSCs model of Alzheimer's disease. Cell Death Discov 8, 1. 10.1038 / s41420-021-00796- 3. Vaillant-Beuchot, L., Mary, A., Pardossi-Piquard, R., Bourgeois, A., Lauritzen, I., Eysert, F., Kinoshita, P.F., Cazareth, J., Badot, C., Fragaki, K., et al. (2021). Accumulation of amyloid precursor protein C-terminal fragments triggers mitochondrial structure, function, and mitophagy defects in Alzheimer's disease models and human brains. Acta Neuropathol 141, 39-65. 10.1007 / s00401-020-02234-7. Cho, D.H., Nakamura, T., Fang, J., Cieplak, P., Godzik, A., Gu, Z., and Lipton, S.A. (2009). S-nitrosylation of Drpl mediates beta-amyloid-related mitochondrial fission and neuronal injury. Science 324, 102-105. 10.1126 / science.1171091. Wang, X., Su, B., Lee, H.G., Li, X., Perry, G., Smith, M.A., and Zhu, X. (2009). Impaired balance of mitochondrial fission and fusion in Alzheimer's disease. J Neurosci 29, 9090- 9103. 10.1523 / JNEUROSCI.1357-09.2009. Hu, C., Huang, Y , and Li, L. (2017). Drpl -Dependent Mitochondrial Fission Plays Critical Roles in Physiological and Pathological Progresses in Mammals. Int J Mol Sci 18. 10.3390 / ijmsl8010144. Perneczky, R., Guo, L.H., Kagerbauer, S.M., Werle, L., Kurz, A., Martin, J., and Alexopoulos, P. (2013). Soluble amyloid precursor protein beta as blood-based biomarker of Alzheimer's disease. Transl Psychiatry 3, e227. 10.1038 / tp.2013.11. Li, Q.X., Fuller, S.J., Beyreuther, K., and Masters, C.L. (1999). The amyloid precursor protein of Alzheimer disease in human brain and blood. J Leukoc Biol 66, 567-574. 10.1002 / jlb.66.4.567. Delvaux, E., Bentley, K., Stubbs, V., Sabbagh, M., and Coleman, P.D. (2013). Differential processing of amyloid precursor protein in brain and in peripheral blood leukocytes. Neurobiol Aging 34, 1680-1686. 10.1016 / j.neurobiolaging.2012.12.004. Lopez Sanchez, M.I.G., Waugh, H.S., Tsatsanis, A., Wong, B.X., Crowston, J.G., Duce, J.A., and Trounce, I. A. (2017). Amyloid precursor protein drives down-regulation of mitochondrial oxidative phosphorylation independent of amyloid beta. Sci Rep 7, 9835. 10.1038 / s41598-017-10233-0. Atamna, H., and Frey, W.H., 2nd (2007). Mechanisms of mitochondrial dysfunction and energy deficiency in Alzheimer's disease. Mitochondrion 7, 297-310.

[0151] 10.1016 / j.mito.2007.06.001. Oddo, S., Caccamo, A., Shepherd, J.D., Murphy, M.P., Golde, T.E., Kayed, R., Metherate, R., Mattson, M.P., Akbari, Y., and LaFerla, F.M. (2003). Triple-transgenic model of Alzheimer's disease with plaques and tangles: intracellular Abeta and synaptic dysfunction. Neuron 39, 409-421. 10.1016 / s0896-6273(03)00434-3. Haeryfar, S.M., and Hoskin, D.W. (2004). Thy-1 : more than a mouse pan-T cell marker. J Immunol 173, 3581-3588. 10.4049 / jimmunol.173.6.3581. Jankowsky, J.L., Fadale, D.J., Anderson, J., Xu, G.M., Gonzales, V., Jenkins, N.A., Copeland, N.G., Lee, M.K., Younkin, L.H., Wagner, S.L., et al. (2004). Mutant presenilins specifically elevate the levels of the 42 residue beta-amyloid peptide in vivo: evidence for augmentation of a 42-specific gamma secretase. Hum Mol Genet 13, 159-170. 10.1093 / hmg / ddh019. Oleinik, N., Albayram, O., Kassir, M.F., Atilgan, F.C., Walton, C., Karakaya, E., Kurtz, J., Alekseyenko, A., Alsudani, H., Sheridan, M., et al. (2023). Alterations of lipid-mediated mitophagy result in aging-dependent sensorimotor defects. Aging Cell, el3954. 10.1111 / acel.13954. Anandatheerthavarada, H.K., Biswas, G., Robin, M.A., and Avadhani, N.G. (2003). Mitochondrial targeting and a novel transmembrane arrest of Alzheimer's amyloid precursor protein impairs mitochondrial function in neuronal cells. J Cell Biol 161, 41-54. 10.1083 / jcb.200207030. Liu, J., Huang, X., Withers, B.R., Blalock, E., Liu, K., and Dickson, R.C. (2013). Reducing sphingolipid synthesis orchestrates global changes to extend yeast lifespan. Aging Cell 12, 833-841. 10.1111 / acel.12107. Montoliu, I., Scherer, M., Beguelin, F., DaSilva, L., Mari, D., Salvioli, S., Martin, F.P., Capri, M., Bucci, L., Ostan, R., et al. (2014). Serum profiling of healthy aging identifies phospho- and sphingolipid species as markers of human longevity. Aging (Albany NY) 6, 9-25. 10.18632 / aging.100630. Baudier, J. (2018). ATAD3 proteins: brokers of a mitochondria-endoplasmic reticulum connection in mammalian cells. Biol Rev Camb Philos Soc 93, 827-844. 10.1111 / brv.12373. Braak, H., and Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 82, 239-259. 10.1007 / BF00308809. Gu, L., and Guo, Z. (2013). Alzheimer's Abeta42 and Abeta40 peptides form interlaced amyloid fibrils. J Neurochem 126, 305-311. 10.1111 / jnc.12202. Perez-Grijalba, V., Romero, J., Pesini, P., Sarasa, L., Monleon, I., San-Jose, I., Arbizu, J., Martinez-Lage, P., Munuera, J., Ruiz, A., et al. (2019). Plasma Abeta42 / 40 Ratio Detects Early Stages of Alzheimer's Disease and Correlates with CSF and Neuroimaging Biomarkers in the AB255 Study. J Prev Alzheimers Dis 6, 34-41. 10.14283 / jpad.2018.41. Blatnik, M., Thorpe, S.R., and Baynes, J.W. (2008). Succination of proteins by fumarate: mechanism of inactivation of glyceraldehyde-3 -phosphate dehydrogenase in diabetes. Ann N Y Acad Sci 1126, 272-275. 10.1196 / annals.l433.047. Seirafi, M., Kozlov, G., and Gehring, K. (2015). Parkin structure and function. FEBS J 282, 2076-2088. 10.1111 / febs.13249. Alderson, N.L., Wang, Y., Blatnik, M., Frizzell, N., Walla, M.D., Lyons, T.J., Alt, N., Carson, J. A., Nagai, R., Thorpe, S.R., and Baynes, J.W. (2006). S-(2-Succinyl)cysteine: a novel chemical modification of tissue proteins by a Krebs cycle intermediate. Arch Biochem Biophys 450, 1-8. 10.1016 / j.abb.2006.03.005. Swerdlow, R.H. (2018). Mitochondria and Mitochondrial Cascades in Alzheimer's Disease. J Alzheimers Dis 62, 1403-1416. 10.3233 / JAD-170585. Cho, S.M., Lee, S., Yang, S.H., Kim, H.Y., Lee, M.J., Kim, H.V., Kim, J., Baek, S., Yun, J., Kim, D., et al. (2016). Age-dependent inverse correlations in CSF and plasma amyloid- beta(l-42) concentrations prior to amyloid plaque deposition in the brain of 3xTg-AD mice. Sci Rep 6, 20185. 10.1038 / srep20185. van Oijen, M., Hofman, A., Soares, H.D., Koudstaal, P.J., and Breteler, M.M. (2006). Plasma Abeta(l-40) and Abeta(l-42) and the risk of dementia: a prospective case-cohort study. Lancet Neurol 5, 655-660. 10.1016 / S 1474-4422(06)70501-4. Yang, Y.H., Huang, L.C., Hsieh, S.W., and Huang, L.J. (2020). Dynamic Blood Concentrations of Abeta(l-40) and Abeta(l-42) in Alzheimer's Disease. Front Cell Dev Biol 8, 768. 10.3389 / fcell.2020.00768. Pereira, C., Santos, M.S., and Oliveira, C. (1998). Mitochondrial function impairment induced by amyloid beta-peptide on PC12 cells. Neuroreport 9, 1749-1755. 10.1097 / 00001756-199806010-00015. Cardoso, S.M., Santos, S., Swerdlow, R.H., and Oliveira, C.R. (2001). Functional mitochondria are required for amyloid beta-mediated neurotoxicity. FASEB J 15, 1439- 1441. 10.1096 / fj.00-0561fje. Peralta, S., Goffart, S., Williams, S.L., Diaz, F., Garcia, S., Nissanka, N., Area-Gomez, E., Pohjoismaki, J., and Moraes, C.T. (2018), ATAD3 controls mitochondrial cristae structure in mouse muscle, influencing mtDNA replication and cholesterol levels. J Cell Sci 131. 10.1242 / jcs.217075. Sen, A., Kallabis, S., Gaedke, F., Jungst, C., Boix, J., Nuchel, J., Maliphol, K., Hofmann, J., Schauss, A.C., Kruger, M., et al. (2022). Mitochondrial membrane proteins and VPS35 orchestrate selective removal of mtDNA. Nat Commun 13, 6704. 10.1038 / s41467-022- 34205-9. Cheng, J., Yan, J., Liu, Y., Shi, J., Wang, H., Zhou, H., Zhou, Y., Zhang, T., Zhao, L., Meng, X., et al. (2023). Cancer-cell-derived fumarate suppresses the anti-tumor capacity of CD8(+) T cells in the tumor microenvironment. Cell Metab 35, 961-978 e910. 10.1016 / j.cmet.2023.04.017. Luckel, C., Picard, F , Raifer, H., Campos Carrascosa, L., Guralnik, A., Zhang, Y., Klein, M., Bittner, S., Steffen, F., Moos, S., et al. (2019). IL-17(+) CD8(+) T cell suppression by dimethyl fumarate associates with clinical response in multiple sclerosis. Nat Commun 10, 5722. 10.1038 / s41467-019- 13731-z. Landry, F., Chan, C.C., Huang, Z., Leclair, G., Li, C.S., Oballa, R , Zhang, L., and Bateman, K. (2011). Plasma-based approach to measure target engagement for livertargeting stearoyl-CoA desaturase 1 inhibitors. J Lipid Res 52, 1494-1499. 10.1194 / jlr.M013177. Zheng, R.H., Zhang, Y.B., Qiu, F.N., Liu, Z.H., Han, Y., Huang, R., Zhao, Y., Yao, P.,

[0152] Qiu, Y., and Ren, J. (2021). NF-kappaB pathway play a role in SCD1 deficiency-induced ceramide de novo synthesis. Cancer Biol Ther 22, 164-174.

[0153] 10.1080 / 15384047.2021.1883414. Kim, M.J., Hwang, J.W., Yun, C.K., Lee, Y., and Choi, Y.S. (2018). Delivery of exogenous mitochondria via centrifugation enhances cellular metabolic function. Sci Rep 8, 3330. 10.1038 / s41598-018-21539-y. Overwijk, W.W., Theoret, M.R., Finkelstein, S.E., Surman, D.R., de Jong, L.A., Vyth- Dreese, F A., Dellemijn, T.A., Antony, P.A., Spiess, P.J., Palmer, D.C., et al. (2003). Tumor regression and autoimmunity after reversal of a functionally tolerant state of self- reactive CD8+ T cells. J Exp Med 198, 569-580. 10.1084 / jem.20030590. Nganga, R., Oleinik, N., Kim, J., Selvam, S.P., De Palma, R., Johnson, K.A., Parikh, R.Y., Gangaraju, V., Peterson, Y., Dany, M., et al. (2019). Receptor-interacting Ser / Thr kinase 1 (RIPK1) and myosin IIA-dependent ceramidosomes form membrane pores that mediate blebbing and necroptosis. J Biol Chem 294, 502-519. 10.1074 / jbc. RAI 18.005865. Janneh, A.H., Kassir, M.F., Dwyer, C.J., Chakraborty, P., Pierce, J.S., Flume, P.A., Li, H., Nadig, S.N., Mehrotra, S., and Ogretmen, B. (2021). Alterations of lipid metabolism provide serologic biomarkers for the detection of asymptomatic versus symptomatic COVID- 19 patients. Sci Rep 77, 14232. 10.1038 / s41598-021-93857-7. Ji, Y., Abrams, N., Zhu, W., Salinas, E., Yu, Z., Palmer, D.C., Jailwala, P., Franco, Z., Roychoudhuri, R , Stahlberg, E., et al. (2014). Identification of the genomic insertion site of Pmel-1 TCR alpha and beta transgenes by next-generation sequencing. PLoS One 9, e96650. 10.1371 / joumal. pone.0096650. Caicedo, A., Fritz, V., Brondello, J.M., Ayala, M., Dennemont, I., Abdellaoui, N., de Fraipont, F., Moisan, A., Prouteau, C.A., Boukhaddaoui, H., et al. (2015). MitoCeption as a new tool to assess the effects of mesenchymal stem / stromal cell mitochondria on cancer cell metabolism and function. Sci Rep 5, 9073. 10.1038 / srep09073.

[0154] 95. Cohen, J.W., Monheit, A.C., Beauregard, K.M., Cohen, S.B., Lefkowitz, D.C., Potter, D.E., Sommers, J.P., Taylor, A.K., and Arnett, R.H., 3rd (1996). The Medical Expenditure Panel Survey: a national health information resource. Inquiry 33, 373-389.

[0155] 96. Caliendo, M., and Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys 22, 31-72.

[0156] It is to be understood that the invention is not limited to the particular embodiments of the invention described above, as variations of the particular embodiments may be made and still fall within the scope of the appended claims.

Claims

CLAIMS1. A method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of overexpressing Alzheimer’s disease-associated APP in the T-cells.

2. A method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of treating the T-cells with exogenous A04O.

3. A method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of treating the T-cells with fumarate.

4. A method of inhibiting aging-stress mediated and ceramide-dependent hyperactivated mitophagy in T-cells, comprising the step of transferring mitochondria from AD T-cells to non- AD T-cells.

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