FOXO1 enhances CAR T cell stemness, metabolic fitness and efficacy.

Chimeric antigen receptor (CAR) T cell therapy has transformed the treatment of haematological malignancies such as acute lymphoblastic leukaemia, B cell lymphoma and multiple myeloma1-4, but the efficacy of CAR T cell therapy in solid tumours has been limited5. This is owing to a number of factors, including the immunosuppressive tumour microenvironment that gives rise to poorly persisting and metabolically dysfunctional T cells. Analysis of anti-CD19 CAR T cells used clinically has shown that positive treatment outcomes are associated with a more 'stem-like' phenotype and increased mitochondrial mass6-8. We therefore sought to identify transcription factors that could enhance CAR T cell fitness and efficacy against solid tumours. Here we show that overexpression of FOXO1 promotes a stem-like phenotype in CAR T cells derived from either healthy human donors or patients, which correlates with improved mitochondrial fitness, persistence and therapeutic efficacy in vivo. This work thus reveals an engineering approach to genetically enforce a favourable metabolic phenotype that has high translational potential to improve the efficacy of CAR T cells against solid tumours.

Integrative genomics analysis reveals a 21q22.11 locus contributing risk to COVID-19.

The systematic identification of host genetic risk factors is essential for the understanding and treatment of coronavirus disease 2019 (COVID-19). By performing a meta-analysis of two independent genome-wide association summary datasets (N = 680 128), a novel locus at 21q22.11 was identified to be associated with COVID-19 infection (rs9976829 in IFNAR2-IL10RB, odds ratio = 1.16, 95% confidence interval = 1.09-1.23, P = 2.57 × 10-6). The rs9976829 represents a strong splicing quantitative trait locus for both IFNAR2 and IL10RB genes, especially in lung tissue (P = 1.8 × 10-24). Integrative genomics analysis of combining genome-wide association study with expression quantitative trait locus data showed the expression variations of IFNAR2 and IL10RB have prominent effects on COVID-19 in various types of tissues, especially in lung tissue. The majority of IFNAR2-expressing cells were dendritic cells (40%) and plasmacytoid dendritic cells (38.5%), and IL10RB-expressing cells were mainly nonclassical monocytes (29.6%). IFNAR2 and IL10RB are targeted by several interferons-related drugs. Together, our results uncover 21q22.11 as a novel susceptibility locus for COVID-19, in which individuals with G alleles of rs9976829 have a higher probability of COVID-19 susceptibility than those with non-G alleles.

Genome-wide cell-free DNA methylation analyses improve accuracy of non-invasive diagnostic imaging for early-stage breast cancer.

Early detection is crucial to improve breast cancer (BC) patients' outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78-0.79 to 0.93-0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms.

SFRP4 drives invasion in gastric cancer and is an early predictor of recurrence.

OBJECTIVE: Gastric cancer patients generally have a poor outcome, particularly those with advanced-stage disease which is defined by the increased invasion of cancer locally and is associated with higher metastatic potential. This study aimed to identify genes that were functional in the most fundamental hallmark of cancer, namely invasion. We then wanted to assess their value as biomarkers of gastric cancer progression and recurrence. DESIGN: Data from a cohort of patients profiled on cDNA expression arrays was interrogated using K-means analysis. This genomic approach classified the data based on patterns of gene expression allowing the identification of the genes most correlated with the invasion of GC. We evaluated the functional role of a key protein from this analysis in invasion and as a biomarker of recurrence after curative resection. RESULTS: Expression of secreted frizzled-related protein 4 (SFRP4) was identified as directly proportional to gastric cancer invasion. This finding was validated in multiple, independent datasets and its functional role in invasion was also confirmed using invasion assays. A change in serum levels of SFRP4 after curative resection, when coupled with AJCC stage, can accurately predict the risk of disease recurrence after curative therapy in an assay we termed PredictR. CONCLUSIONS: This simple ELISA-based assay can help predict recurrence of disease after curative gastric cancer surgery irrespective of adjuvant therapy. The results require further evaluation in a prospective trial but would help in the rational prescription of cancer therapies and surveillance to prevent under or over treatment of patients after curative resection.

Single cell sequencing analysis identifies genetics-modulated ORMDL3+ cholangiocytes having higher metabolic effects on primary biliary cholangitis.

BACKGROUND: Primary biliary cholangitis (PBC) is a classical autoimmune disease, which is highly influenced by genetic determinants. Many genome-wide association studies (GWAS) have reported that numerous genetic loci were significantly associated with PBC susceptibility. However, the effects of genetic determinants on liver cells and its immune microenvironment for PBC remain unclear. RESULTS: We constructed a powerful computational framework to integrate GWAS summary statistics with scRNA-seq data to uncover genetics-modulated liver cell subpopulations for PBC. Based on our multi-omics integrative analysis, 29 risk genes including ORMDL3, GSNK2B, and DDAH2 were significantly associated with PBC susceptibility. By combining GWAS summary statistics with scRNA-seq data, we found that cholangiocytes exhibited a notable enrichment by PBC-related genetic association signals (Permuted P < 0.05). The risk gene of ORMDL3 showed the highest expression proportion in cholangiocytes than other liver cells (22.38%). The ORMDL3+ cholangiocytes have prominently higher metabolism activity score than ORMDL3- cholangiocytes (P = 1.38 × 10-15). Compared with ORMDL3- cholangiocytes, there were 77 significantly differentially expressed genes among ORMDL3+ cholangiocytes (FDR < 0.05), and these significant genes were associated with autoimmune diseases-related functional terms or pathways. The ORMDL3+ cholangiocytes exhibited relatively high communications with macrophage and monocyte. Compared with ORMDL3- cholangiocytes, the VEGF signaling pathway is specific for ORMDL3+ cholangiocytes to interact with other cell populations. CONCLUSIONS: To the best of our knowledge, this is the first study to integrate genetic information with single cell sequencing data for parsing genetics-influenced liver cells for PBC risk. We identified that ORMDL3+ cholangiocytes with higher metabolism activity play important immune-modulatory roles in the etiology of PBC.

First demonstration of gold nanorods-mediated photodynamic therapeutic destruction of tumors via near infra-red light activation.

Previously, a large volume of papers reports that gold nanorods (Au NRs) are able to effectively kill cancer cells upon high laser doses (usually 808 nm, 1-48 W/cm²) irradiation, leading to hyperthermia-induced destruction of cancer cells, i.e, photothermal therapy (PTT) effects. Combination of Au NRs-mediated PTT and organic photosensitizers-mediated photodynamic therapy (PDT) were also reported to achieve synergistic PTT and PDT effects on killing cancer cells. Herein, we demonstrate for the first time that Au NRs alone can sensitize formation of singlet oxygen (¹O2) and exert dramatic PDT effects on complete destrcution of tumors in mice under very low LED/laser doses of single photon NIR (915 nm, <130 mW/cm²) light excitation. By changing the NIR light excitation wavelengths, Au NRs-mediated phototherapeutic effects can be switched from PDT to PTT or combination of both. Both PDT and PTT effects were confirmed by measurements of reactive oxygen species (ROS) and heat shock protein (HSP 70), singlet oxygen sensor green (SOSG) sensing, and sodium azide quenching in cellular experiments. In vivo mice experiments further show that the PDT effect via irradiation of Au NRs by 915 nm can destruct the B16F0 melanoma tumor in mice far more effectively than doxorubicin (a clinically used anti-cancer drug) as well as the PTT effect (via irradiation of Au NRs by 780 nm light). In addition, we show that Au NRs can emit single photon-induced fluorescence to illustrate their in vivo locations/distribution.

Immunological responses to brain metastasis stereotactic radiosurgery in patient-matched longitudinal blood and tumour samples.

Background: Stereotactic radiosurgery (SRS) is highly effective as focal treatment for brain metastases (BrMs), but whether it can promote anti-tumour immune responses that synergise with immunotherapy remains unclear. We investigated this by examining blood samples from a clinical trial for HER2-amplified breast cancer (HER2-BC) BrMs, matched with longitudinal HER2-BC BrM samples resected from the same location in the same patient. Methods: Blood samples from 10 patients taken pre- and 7-14 days post-SRS were analysed by mass and flow cytometry. One patient received pre-operative SRS for a BrM that recurred 7 months after resection, followed by planned re-resection 8 days post-SRS. Pre- and post-SRS tumours from this patient were analysed by bulk RNAseq, multiplex immunohistochemistry (mIHC), and TCR sequencing. Results: Monocytes, central memory CD8+ T and regulatory T cells were enriched in blood post-SRS, together with increased MHC-II expression on monocytes, conventional DCs, and monocytic MDSCs. In tumour, SRS upregulated antigen presentation, T cell proliferation and T cell co-stimulation signatures, alongside an influx of tumour-associated macrophages (TAMs) and CD4+ T cells. Specifically, TAMs and CD4+ T cells, but not CD8+ T cells, demonstrated spatial co-localisation post-SRS. These TAMs were lowly PD-L1 expressing, but CD4+ T cells showed increased PD-1 expression. A sizeable proportion of T cell clonotypes were retained post-SRS, and four clones demonstrated significant, non-stochastic expansion. Conclusion: Systemic and local immunological changes in this homogenous patient cohort suggest that SRS may facilitate MHC-II-restricted T cell priming responses involving the monocyte-macrophage lineage and CD4+ T cells, which should be further explored.

Spatial analysis with SPIAT and spaSim to characterize and simulate tissue microenvironments.

Spatial proteomics technologies have revealed an underappreciated link between the location of cells in tissue microenvironments and the underlying biology and clinical features, but there is significant lag in the development of downstream analysis methods and benchmarking tools. Here we present SPIAT (spatial image analysis of tissues), a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial simulator), a simulator of tissue spatial data. SPIAT includes multiple colocalization, neighborhood and spatial heterogeneity metrics to characterize the spatial patterns of cells. Ten spatial metrics of SPIAT are benchmarked using simulated data generated with spaSim. We show how SPIAT can uncover cancer immune subtypes correlated with prognosis in cancer and characterize cell dysfunction in diabetes. Our results suggest SPIAT and spaSim as useful tools for quantifying spatial patterns, identifying and validating correlates of clinical outcomes and supporting method development.

CRISPR-Cas9 screening identifies an IRF1-SOCS1-mediated negative feedback loop that limits CXCL9 expression and antitumor immunity.

CXCL9 expression is a strong predictor of response to immune checkpoint blockade therapy. Accordingly, we sought to develop therapeutic strategies to enhance the expression of CXCL9 and augment antitumor immunity. To perform whole-genome CRISPR-Cas9 screening for regulators of CXCL9 expression, a CXCL9-GFP reporter line is generated using a CRISPR knockin strategy. This approach finds that IRF1 limits CXCL9 expression in both tumor cells and primary myeloid cells through induction of SOCS1, which subsequently limits STAT1 signaling. Thus, we identify a subset of STAT1-dependent genes that do not require IRF1 for their transcription, including CXCL9. Targeting of either IRF1 or SOCS1 potently enhances CXCL9 expression by intratumoral macrophages, which is further enhanced in the context of immune checkpoint blockade therapy. We hence show a non-canonical role for IRF1 in limiting the expression of a subset of STAT1-dependent genes through induction of SOCS1.

A2AR eGFP reporter mouse enables elucidation of A2AR expression dynamics during anti-tumor immune responses.

There is significant clinical interest in targeting adenosine-mediated immunosuppression, with several small molecule inhibitors having been developed for targeting the A2AR receptor. Understanding of the mechanism by which A2AR is regulated has been hindered by difficulty in identifying the cell types that express A2AR due to a lack of robust antibodies for these receptors. To overcome this limitation, here an A2AR eGFP reporter mouse is developed, enabling the expression of A2AR during ongoing anti-tumor immune responses to be assessed. This reveals that A2AR is highly expressed on all tumor-infiltrating lymphocyte subsets including Natural Killer (NK) cells, NKT cells, γδ T cells, conventional CD4+ and CD8+ T lymphocytes and on a MHCIIhiCD86hi subset of type 2 conventional dendritic cells. In response to PD-L1 blockade, the emergence of PD-1+A2AR- cells correlates with successful therapeutic responses, whilst IL-18 is identified as a cytokine that potently upregulates A2AR and synergizes with A2AR deficiency to improve anti-tumor immunity. These studies provide insight into the biology of A2AR in the context of anti-tumor immunity and reveals potential combination immunotherapy approaches.

Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19.

BACKGROUND: Understanding the host genetic architecture and viral immunity contributes to the development of effective vaccines and therapeutics for controlling the COVID-19 pandemic. Alterations of immune responses in peripheral blood mononuclear cells play a crucial role in the detrimental progression of COVID-19. However, the effects of host genetic factors on immune responses for severe COVID-19 remain largely unknown. METHODS: We constructed a computational framework to characterize the host genetics that influence immune cell subpopulations for severe COVID-19 by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets containing healthy controls and patients with mild, moderate, and severe symptom (N = 606,534 cells). We collected 10 predefined gene sets including inflammatory and cytokine genes to calculate cell state score for evaluating the immunological features of individual immune cells. RESULTS: We found that 34 risk genes were significantly associated with severe COVID-19, and the number of highly expressed genes increased with the severity of COVID-19. Three cell subtypes that are CD16+monocytes, megakaryocytes, and memory CD8+T cells were significantly enriched by COVID-19-related genetic association signals. Notably, three causal risk genes of CCR1, CXCR6, and ABO were highly expressed in these three cell types, respectively. CCR1+CD16+monocytes and ABO+ megakaryocytes with significantly up-regulated genes, including S100A12, S100A8, S100A9, and IFITM1, confer higher risk to the dysregulated immune response among severe patients. CXCR6+ memory CD8+ T cells exhibit a notable polyfunctionality including elevation of proliferation, migration, and chemotaxis. Moreover, we observed an increase in cell-cell interactions of both CCR1+ CD16+monocytes and CXCR6+ memory CD8+T cells in severe patients compared to normal controls among both PBMCs and lung tissues. The enhanced interactions of CXCR6+ memory CD8+T cells with epithelial cells facilitate the recruitment of this specific population of T cells to airways, promoting CD8+T cell-mediated immunity against COVID-19 infection. CONCLUSIONS: We uncover a major genetics-modulated immunological shift between mild and severe infection, including an elevated expression of genetics-risk genes, increase in inflammatory cytokines, and of functional immune cell subsets aggravating disease severity, which provides novel insights into parsing the host genetic determinants that influence peripheral immune cells in severe COVID-19.

DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.

BACKGROUND: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and risk prediction models for prioritizing genetic testing among breast cancer patients do not meet the demands of clinical practice due to insufficient accuracy. METHODS: The study population comprised 3041 breast cancer patients enrolled from seven hospitals between October 2017 and 11 August 2019, who underwent germline genetic testing of 50 cancer predisposition genes (CPGs). Associations among GPVs in different CPGs and endophenotypes were evaluated using a case-control analysis. A phenotype-based GPV risk prediction model named DNA-repair Associated Breast Cancer (DrABC) was developed based on hierarchical neural network architecture and validated in an independent multicenter cohort. The predictive performance of DrABC was compared with currently used models including BRCAPRO, BOADICEA, Myriad, PENN II, and the NCCN criteria. RESULTS: In total, 332 (11.3%) patients harbored GPVs in CPGs, including 134 (4.6%) in BRCA2, 131 (4.5%) in BRCA1, 33 (1.1%) in PALB2, and 37 (1.3%) in other CPGs. GPVs in CPGs were associated with distinct endophenotypes including the age at diagnosis, cancer history, family cancer history, and pathological characteristics. We developed a DrABC model to predict the risk of GPV carrier status in BRCA1/2 and other important CPGs. In predicting GPVs in BRCA1/2, the performance of DrABC (AUC = 0.79 [95% CI, 0.74-0.85], sensitivity = 82.1%, specificity = 63.1% in the independent validation cohort) was better than that of previous models (AUC range = 0.57-0.70). In predicting GPVs in any CPG, DrABC (AUC = 0.74 [95% CI, 0.69-0.79], sensitivity = 83.8%, specificity = 51.3% in the independent validation cohort) was also superior to previous models in their current versions (AUC range = 0.55-0.65). After training these previous models with the Chinese-specific dataset, DrABC still outperformed all other methods except for BOADICEA, which was the only previous model with the inclusion of pathological features. The DrABC model also showed higher sensitivity and specificity than the NCCN criteria in the multi-center validation cohort (83.8% and 51.3% vs. 78.8% and 31.2%, respectively, in predicting GPVs in any CPG). The DrABC model implementation is available online at http://gifts.bio-data.cn/ . CONCLUSIONS: By considering the distinct endophenotypes associated with different CPGs in breast cancer patients, a phenotype-driven prediction model based on hierarchical neural network architecture was created for identification of hereditary breast cancer. The model achieved superior performance in identifying GPV carriers among Chinese breast cancer patients.

The Role of Innate Immune Cells in Tumor Invasion and Metastasis.

Metastasis is considered one of the hallmarks of cancer and enhanced tumor invasion and metastasis is significantly associated with cancer mortality. Metastasis occurs via a series of integrated processes involving tumor cells and the tumor microenvironment. The innate immune components of the microenvironment have been shown to engage with tumor cells and not only regulate their proliferation and survival, but also modulate the surrounding environment to enable cancer progression. In the era of immune therapies, it is critical to understand how different innate immune cell populations are involved in this process. This review summarizes recent literature describing the roles of innate immune cells during the tumor metastatic cascade.

Evaluation of the association of heterozygous germline variants in NTHL1 with breast cancer predisposition: an international multi-center study of 47,180 subjects.

Bi-allelic loss-of-function (LoF) variants in the base excision repair (BER) gene NTHL1 cause a high-risk hereditary multi-tumor syndrome that includes breast cancer, but the contribution of heterozygous variants to hereditary breast cancer is unknown. An analysis of 4985 women with breast cancer, enriched for familial features, and 4786 cancer-free women revealed significant enrichment for NTHL1 LoF variants. Immunohistochemistry confirmed reduced NTHL1 expression in tumors from heterozygous carriers but the NTHL1 bi-allelic loss characteristic mutational signature (SBS 30) was not present. The analysis was extended to 27,421 breast cancer cases and 19,759 controls from 10 international studies revealing 138 cases and 93 controls with a heterozygous LoF variant (OR 1.06, 95% CI: 0.82-1.39) and 316 cases and 179 controls with a missense variant (OR 1.31, 95% CI: 1.09-1.57). Missense variants selected for deleterious features by a number of in silico bioinformatic prediction tools or located within the endonuclease III functional domain showed a stronger association with breast cancer. Somatic sequencing of breast cancers from carriers indicated that the risk associated with NTHL1 appears to operate through haploinsufficiency, consistent with other described low-penetrance breast cancer genes. Data from this very large international multicenter study suggests that heterozygous pathogenic germline coding variants in NTHL1 may be associated with low- to moderate- increased risk of breast cancer.

Benchmarking algorithms for pathway activity transformation of single-cell RNA-seq data.

Biological pathway analysis provides new insights for cell clustering and functional annotation from single-cell RNA sequencing (scRNA-seq) data. Many pathway analysis algorithms have been developed to transform gene-level scRNA-seq data into functional gene sets representing pathways or biological processes. Here, we collected seven widely-used pathway activity transformation algorithms and 32 available datasets based on 16 scRNA-seq techniques. We proposed a comprehensive framework to evaluate their accuracy, stability and scalability. The assessment of scRNA-seq preprocessing showed that cell filtering had the less impact on scRNA-seq pathway analysis, while data normalization of sctransform and scran had a consistent well impact across all tools. We found that Pagoda2 yielded the best overall performance with the highest accuracy, scalability, and stability. Meanwhile, the tool PLAGE exhibited the highest stability, as well as moderate accuracy and scalability.

High-dimensional analyses reveal a distinct role of T-cell subsets in the immune microenvironment of gastric cancer.

OBJECTIVES: To facilitate disease prognosis and improve precise immunotherapy of gastric cancer (GC) patients, a comprehensive study integrating immune cellular and molecular analyses on tumor tissues and peripheral blood was performed. METHODS: The association of GC patients' outcomes and the immune context of their tumors was explored using multiplex immunohistochemistry (mIHC) and transcriptome profiling. Potential immune dysfunction mechanism/s in the tumors on the systemic level was further examined using mass cytometry (CyTOF) in complementary peripheral blood from selected patients. GC cohorts with mIHC and gene expression profiling data were also used as validation cohorts. RESULTS: Increased CD4+FOXP3+ T-cell density in the GC tumor correlated with prolonged survival. Interestingly, CD4+FOXP3+ T cells had a close interaction with CD8+ T cells rather than tumor cells. High densities of CD4+FOXP3+ T cells and CD8+ T cells (High-High) independently predicted prolonged patient survival. Furthermore, the interferon-gamma (IFN-γ) gene signature and PDL1 expression were up-regulated in this group. Importantly, a subgroup of genomically stable (GS) tumors and tumors with chromosomal instability (CIN) within this High-High group also had excellent survival. The High-High GS/CIN tumors were coupled with increased frequencies of Tbet+CD4+ T cells and central memory CD4+ T cells in the peripheral blood. CONCLUSION: These novel findings identify the combination of CD8+ T cells and FOXP3+CD4+ T cells as a significant prognostic marker for GC patients, which also could potentially be targeted and applied in the combination therapy with immune checkpoint blockades in precision medicine.

Ag-NPs/MWCNT composite-modified silver-epoxy paste with improved thermal conductivity.

Heat dissipation is a critical issue in high-performance electronics, which needs to be solved, and an electronic paste is a good choice to solve this issue. In this paper, silver nanoparticles/multi-walled carbon nanotube (Ag-NPs/MWCNT) composites were prepared by the chemical process for the modification of electronic pastes. The micromorphology and spectral analysis of the as-prepared Ag-NPs/MWCNT composites indicated that Ag-NPs were uniformly distributed on the MWCNT surfaces with high distribution densities; the average size of Ag-NPs was estimated to be 8.29 nm. The as-obtained Ag-NPs/MWCNT composites were then added to a silver-epoxy paste. Field emission scanning electron microscopy (FESEM), thermogravimetry (TG) and thermal conductivity analyses suggested the incorporation of Ag-NPs/MWCNT composites in the silver-epoxy paste; Ag flakes were better connected by Ag-NPs/MWCNTs, which improved the thermal conductivity of the paste from 0.73 to 0.96 W m-1 K-1. However, more weight loss was observed when Ag-NPs/MWCNTs were incorporated in the silver-epoxy paste. Overall, the addition of Ag-NPs/MWCNTs into the silver-epoxy paste increased the thermal conductivity, which can be applied to high-performance electronics.

Macrophage spatial heterogeneity in gastric cancer defined by multiplex immunohistochemistry.

Tumor-associated macrophages (TAMs), one of the most abundant immune components in gastric cancer (GC), are difficult to characterize due to their heterogeneity. Multiple approaches have been used to elucidate the issue, however, due to the tissue-destructive nature of most of these methods, the spatial distribution of TAMs in situ remains unclear. Here we probe the relationship between tumor context and TAM heterogeneity by multiplex immunohistochemistry of 56 human GC cases. Using distinct expression marker profiles on TAMs, we report seven predominant populations distributed between tumor and non-tumor tissue. TAM population-associated gene signatures reflect their heterogeneity and polarization in situ. Increased density of CD163+ (CD206-) TAMs with concurrent high CD68 expression is associated with upregulated immune-signaling and improved patient survival by univariate, but not multivariate analysis. CD68-only and CD206+ TAMs are correlated with high PDL1 expression.

Tumor-Infiltrating Lymphocyte Function Predicts Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

PURPOSE: The presence of tumor-infiltrating lymphocytes (TILs) in tumors is superior to conventional pathologic staging in predicting patient outcome. However, their presence does not define TIL functionality. Here we developed an assay that tests TIL cytotoxicity in patients with locally advanced rectal cancer before definitive treatment, identifying those who will obtain a pathologic complete response (pCR). We also used the assay to demonstrate the rescue of TIL function after checkpoint inhibition blockade (CIB). PATIENTS AND METHODS: Thirty-four consecutive patients were identified initially, with successful completion of the assay before surgery in those 17 patients who underwent full treatment. An in vitro cytotoxic assay of rectal cancer tumoroids cocultured with patient-matched TILs was established and validated. Newly diagnosed patients were recruited with pretreatment biopsy specimens processed within 1 month. Evaluation of TIL-mediated tumoroid lysis was performed by measuring the mean fluorescence intensity of cell death marker, propidium iodide. CIB (anti-programmed cell death protein 1 [anti-PD-1] antibody) response was also assessed in a subset of patient specimens. RESULTS: Six of the 17 patients achieved an objective pCR on final evaluation of the resected specimen after neoadjuvant chemoradiotherapy. Cytotoxic killing identified the pCR group with a higher mean fluorescence intensity (27,982 [95% CI, 25,340 to 30,625]) compared with the non-pCR cohort (12,428 [95% CI, 9,434 to 15,423]; p < .001). Assessment of the effectiveness of CIB revealed partial restoration of cytotoxicity in TILs with increased PD-1 expression with anti-PD-1 antibody exposure. CONCLUSION: Evaluating TIL function can be undertaken within weeks of the diagnostic biopsy, affording the potential to alter patient management decisions and refine selection for a watch-and-wait protocol. This cytotoxic assay also has the potential to serve as a platform to assist in the additional development of CIB.