OX40/OX40 ligand and its role in precision immune oncology.

Immune checkpoint inhibitors have changed the treatment landscape for various malignancies; however, their benefit is limited to a subset of patients. The immune machinery includes both mediators of suppression/immune evasion, such as PD-1, PD-L1, CTLA-4, and LAG-3, all of which can be inhibited by specific antibodies, and immune-stimulatory molecules, such as T-cell co-stimulatory receptors that belong to the tumor necrosis factor receptor superfamily (TNFRSF), including OX40 receptor (CD134; TNFRSF4), 4-1BB (CD137; TNFRSF9), and glucocorticoid-induced TNFR-related (GITR) protein (CD357; TNFRSF18). In particular, OX40 and its binding ligand OX40L (CD134L; TNFSF4; CD252) are critical for immunoregulation. When OX40 on activated T cells binds OX40L on antigen-presenting cells, T-cell activation and immune stimulation are initiated via enhanced T-cell survival, proliferation and cytotoxicity, memory T-cell formation, and abrogation of regulatory T cell (Treg) immunosuppressive functions. OX40 agonists are in clinical trials both as monotherapy and in combination with other immunotherapy agents, in particular specific checkpoint inhibitors, for cancer treatment. To date, however, only a minority of patients respond. Transcriptomic profiling reveals that OX40 and OX40L expression vary between and within tumor types, and that only ~ 17% of cancer patients have high OX40 and low OX40L, one of the expression patterns that might be theoretically amenable to OX40 agonist enhancement. Taken together, the data suggest that the OX40/OX40L machinery is a critical part of the immune stimulatory system and that understanding endogenous expression patterns of these molecules and co-existing checkpoints merits further investigation in the context of a precision immunotherapy strategy for cancer therapy.

Cancer testis antigen burden (CTAB): a novel biomarker of tumor-associated antigens in lung cancer.

BACKGROUND: Cancer-testis antigens (CTAs) are tumor antigens that are normally expressed in the testes but are aberrantly expressed in several cancers. CTA overexpression drives the metastasis and progression of lung cancer, and is associated with poor prognosis. To improve lung cancer diagnosis, prognostic prediction, and drug discovery, robust CTA identification and quantitation is needed. In this study, we examined and quantified the co-expression of CTAs in lung cancer to derive cancer testis antigen burden (CTAB), a novel biomarker of immunotherapy response. METHODS: Formalin fixed paraffin embedded (FFPE) tumor samples in discovery cohort (n = 5250) and immunotherapy and combination therapy treated non-small cell lung cancer (NSCLC) retrospective (n = 250) cohorts were tested by comprehensive genomic and immune profiling (CGIP), including tumor mutational burden (TMB) and the mRNA expression of 17 CTAs. PD-L1 expression was evaluated by IHC. CTA expression was summed to derive the CTAB score. The median CTAB score for the discovery cohort of 170 was applied to the retrospective cohort as cutoff for CTAB "high" and "low". Biomarker and gene expression correlation was measured by Spearman correlation. Kaplan-Meier survival analyses were used to detect overall survival (OS) differences, and objective response rate (ORR) based on RECIST criteria was compared using Fisher's exact test. RESULTS: The CTAs were highly co-expressed (p < 0.05) in the discovery cohort. There was no correlation between CTAB and PD-L1 expression (R = 0.011, p = 0.45) but some correlation with TMB (R = 0.11, p = 9.2 × 10-14). Kaplan-Meier survival analysis of the immunotherapy-treated NSCLC cohort revealed better OS for the pembrolizumab monotherapy treated patients with high CTAB (p = 0.027). The combination group demonstrated improved OS compared to pembrolizumab monotherapy group (p = 0.04). The pembrolizumab monotherapy patients with high CTAB had a greater ORR than the combination therapy group (p = 0.02). CONCLUSIONS: CTA co-expression can be reliably measured using CGIP in solid tumors. As a biomarker, CTAB appears to be independent from PD-L1 expression, suggesting that CTAB represents aspects of tumor immunogenicity not measured by current standard of care testing. Improved OS and ORR for high CTAB NSCLC patients treated with pembrolizumab monotherapy suggests a unique underlying aspect of immune response to these tumor antigens that needs further investigation.

Clinical and Biologic Correlates of ADORA2A Transcriptomic Expression in Cancer.

ADORA2A (adenosine A2a receptor) and ADORA2B propagate immunoregulatory signals, including restricting both innate and adaptive immunity, though recent data also suggest a tumor suppressor effect in certain settings. We evaluated the RNA expression from 514 tumors in a clinical-grade laboratory; 489 patients with advanced/metastatic disease had clinical outcome correlates. Transcript expression was standardized to internal housekeeping genes and ranked (0-100 scale) relative to 735 specimens from 35 different cancer types. Transcript abundance rank values were defined as "low/moderate" (0-74) or "high" (75-100) percentile RNA expression ranks. Overall, 20.8% of tumors had high ADORA2A (≥75 percentile RNA rank). The greatest proportion of high ADORA2A expressors was found in neuroendocrine and breast cancers and sarcomas, whereas the lowest was found in colorectal and ovarian cancers, albeit with patient-to-patient variability. In multivariable logistic regression analysis, there was a significant positive correlation between high ADORA2A RNA expression and a high expression of the immune checkpoint-related molecules PD-1 (p = 0.015), VISTA (p ≤ 0.001), CD38 (p = 0.031), and CD39 (p ≤ 0.001). In 217 immunotherapy-treated patients, high ADORA2A did not correlate significantly with progression-free (p = 0.51) or overall survival (OS) (p = 0.09) from the initiation of the checkpoint blockade. However, high versus not-high ADORA2A transcript expression correlated with longer OS from the time of advanced/metastatic disease (N = 489 patients; (HR 0.69 (95% CI 0.51-0.95) (p = 0.02)). Therefore, high ADORA2A transcript levels may be a favorable prognostic factor, unrelated to immunotherapy. Importantly, ascertaining co-expression patterns of ADORA2A with PD-1 and VISTA in individual tumors as a basis for the precision co-targeting of ADORA2A and these other checkpoint-related molecules warrants investigation in clinical trials.

Identification of targets for prostate cancer immunotherapy.

BACKGROUND: We performed profiling of the immune microenvironment of castration-resistant (CRPC) and castration-sensitive (CSPC) prostate cancer (PC) in order to identify novel targets for immunotherapy. METHODS: PD-L1 and CD3/CD8 immunohistochemistry, PD-L1/2 fluorescent in situ hybridization, tumor mutation burden, microsatellite instability, and RNA-seq of 395 immune-related genes were performed in 19 CRPC and CSPC. Targeted genomic sequencing and fusion analysis were performed in 17 of these specimens. RESULTS: CD276, PVR, and NECTIN2 were highly expressed in PC. Comparison of CRPC versus CSPC and primary versus metastatic tissue revealed the differential expression of immunostimulatory, immunosuppressive, and epithelial-to-mesenchymal transition (EMT)-related genes. Unsupervised clustering of differentially expressed genes yielded two final clusters best segregated by CRPC and CSPC status. CONCLUSION: CD276 and the alternative checkpoint inhibition PVR/NECTIN2/CD226/TIGIT pathway emerged as relevant to PC checkpoint inhibition target development.

Treatment recommendations to cancer patients in the context of FDA guidance for next generation sequencing.

BACKGROUND: Regulatory approval of next generation sequencing (NGS) by the FDA is advancing the use of genomic-based precision medicine for the therapeutic management of cancer as standard care. Recent FDA guidance for the classification of genomic variants based on clinical evidence to aid clinicians in understanding the actionability of identified variants provided by comprehensive NGS panels has also been set forth. In this retrospective analysis, we interpreted and applied the FDA variant classification guidance to comprehensive NGS testing performed for advanced cancer patients and assessed oncologist agreement with NGS test treatment recommendations. METHODS: NGS comprehensive genomic profiling was performed in a CLIA certified lab (657 completed tests for 646 patients treated at Roswell Park Comprehensive Cancer Center) between June 2016 and June 2017. Physician treatment recommendations made within 120 days post-test were gathered from tested patients' medical records and classified as targeted therapy, precision medicine clinical trial, immunotherapy, hormonal therapy, chemotherapy/radiation, surgery, transplant, or non-therapeutic (hospice, surveillance, or palliative care). Agreement between NGS test report targeted therapy recommendations based on the FDA variant classification and physician targeted therapy treatment recommendations were evaluated. RESULTS: Excluding variants contraindicating targeted therapy (i.e., KRAS or NRAS mutations), at least one variant with FDA level 1 companion diagnostic supporting evidence as the most actionable was identified in 14% of tests, with physicians most frequently recommending targeted therapy (48%) for patients with these results. This stands in contrast to physicians recommending targeted therapy based on test results with FDA level 2 (practice guideline) or FDA level 3 (clinical trial or off label) evidence as the most actionable result (11 and 4%, respectively). CONCLUSIONS: We found an appropriate "dose-response" relationship between the strength of clinical evidence supporting biomarker-directed targeted therapy based on application of FDA guidance for NGS test variant classification, and subsequent treatment recommendations made by treating physicians. In view of recent changes at FDA, it is paramount to define regulatory grounds and medical policy coverage for NGS testing based on this guidance.

The Association of Peripheral Blood Regulatory T-Cell Concentrations With Epithelial Ovarian Cancer: A Brief Report.

OBJECTIVE: There is a mounting body of evidence demonstrating higher percentages of regulatory T (Treg) cells in the peripheral blood of patients with cancer in comparison to healthy controls, but there is a paucity of epidemiological literature characterizing circulating Treg cells among patients with epithelial ovarian cancer (EOC). To investigate the role of peripheral Treg cells in ovarian neoplasms, we conducted a case-control study to characterize circulating concentrations of Treg cells among patients with EOC, women with benign ovarian conditions, and healthy controls without a history of cancer. MATERIALS AND METHODS: Participants were identified for inclusion due to their participation in the Data Bank and BioRepository program at Roswell Park Cancer Institute in Buffalo, NY. Patients included 71 women with a primary diagnosis of EOC and 195 women with a diagnosis of benign ovarian conditions. Controls included 101 age- and race-matched women without a history of cancer. Nonfasting, pretreatment peripheral blood levels of CD3+CD4+CD25+FOXP3+ Treg cells were measured using flow cytometric analyses and expressed as a percentage of total CD3+ cells and as a percentage of total CD3+CD4+ cells. RESULTS: Compared to healthy controls and women with benign ovarian conditions, patients with EOC had significantly higher frequency of Treg cells (P < 0.04). In multivariable logistic regression analyses using Treg frequency expressed as a percentage of CD+3 cells, we observed a significant positive association between Treg cell percentage and EOC risk, with each 1% increase associated with a 37% increased risk of EOC (odds ratio, 1.37; 95% confidence interval, 1.04-1.80). We observed a similar trend when Treg frequency was expressed as a percentage of CD3+CD+4 cells (odds ratio, 1.22; 95% confidence interval, 0.99-1.49). CONCLUSIONS: The current study provides support that peripheral Treg cell frequency is elevated in patients with EOC in comparison to women with benign ovarian conditions and healthy controls.

TIM-3 transcriptomic landscape with clinical and immunomic correlates in cancer.

TIM-3, an inhibitory checkpoint receptor, may invoke anti-PD-1/anti-PD-L1 immune checkpoint inhibitor (ICI) resistance. The predictive impact of TIM-3 RNA expression in various advanced solid tumors among patients treated with ICIs is yet to be determined, and their prognostic significance also remains unexplored. We investigated TIM-3 transcriptomic expression and clinical outcomes. We examined TIM-3 RNA expression data through the OmniSeq database. TIM-3 transcriptomic patterns were calibrated against a reference population (735 tumors), adjusted to internal housekeeping genes, and calculated as percentiles. Overall, 514 patients (31 cancer types; 489 patients with advanced/metastatic disease and clinical annotation) were assessed. Ninety tumors (17.5% of 514) had high (≥75th percentile RNA rank) TIM-3 expression. Pancreatic cancer had the greatest proportion of TIM-3 high expressors (36% of 55 patients). Still, there was variability within cancer types with, for instance, 12.7% of pancreatic cancers harboring low TIM-3 (<25th percentile) levels. High TIM-3 expression independently and significantly correlated with high PD-L2 RNA expression (odds ratio (OR) 9.63, 95% confidence interval (CI) 4.91-19.4, P<0.001) and high VISTA RNA expression (OR 2.71, 95% CI 1.43-5.13, P=0.002), all in multivariate analysis. High TIM-3 RNA did not correlate with overall survival (OS) from time of metastatic disease in the 272 patients who never received ICIs, suggesting that it is not a prognostic factor. However, high TIM-3 expression predicted longer median OS (but not progression-free survival) in 217 ICI-treated patients (P=0.0033; median OS, 2.84 versus 1.21 years (high versus not-high TIM-3)), albeit not retained in multivariable analysis. In summary, TIM-3 RNA expression was variable between and within malignancies, and high levels associated with high PD-L2 and VISTA checkpoints and with pancreatic cancer. Individual tumor immunomic assessment and co-targeting co-expressed checkpoints merits exploration in prospective trials as part of a precision immunotherapy strategy.

High CTLA-4 transcriptomic expression correlates with high expression of other checkpoints and with immunotherapy outcome.

Background: CTLA-4 impedes the immune system's antitumor response. There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents. Objective: To assess the prognostic implications and immunologic correlates of high CTLA-4 in tumors of patients on immunotherapy and those on non-immunotherapy treatments. Design/methods: We evaluated RNA expression levels in a clinical-grade laboratory and clinical correlates of CTLA-4 and other immune checkpoints in 514 tumors, including 489 patients with advanced/metastatic cancers and full outcome annotation. A reference population (735 tumors; 35 histologies) was used to normalize and rank transcript abundance (0-100 percentile) to internal housekeeping gene profiles. Results: The most common tumor types were colorectal (140/514, 27%), pancreatic (55/514, 11%), breast (49/514, 10%), and ovarian cancers (43/514, 8%). Overall, 87 of 514 tumors (16.9%) had high CTLA-4 transcript expression (⩾75th percentile rank). Cancers with the largest proportion of high CTLA-4 transcripts were cervical cancer (80% of patients), small intestine cancer (33.3%), and melanoma (33.3%). High CTLA-4 RNA independently/significantly correlated with high PD-1, PD- L2, and LAG3 RNA levels (and with high PD-L1 in univariate analysis). High CTLA-4 RNA expression was not correlated with survival from the time of metastatic disease [N = 272 patients who never received immune checkpoint inhibitors (ICIs)]. However, in 217 patients treated with ICIs (mostly anti-PD-1/anti-PD- L1), progression-free survival (PFS) and overall survival (OS) were significantly longer among patients with high versus non-high CTLA-4 expression [hazard ratio, 95% confidence interval: 0.6 (0.4-0.9) p = 0.008; and 0.5 (0.3-0.8) p = 0.002, respectively]; results were unchanged when 18 patients who received anti-CTLA-4 were omitted. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy. Conclusion: High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

High CTLA-4 expression and immunotherapy outcome High CTLA-4 expression was not a prognostic factor for survival in patients not receiving ICIs but was a significant positive predictive biomarker for better outcome (PFS and OS) in patients on immunotherapy, perhaps because it correlated with expression of other checkpoints such as PD-1 and PD-L2.

LAG-3 transcriptomic expression correlates linearly with other checkpoints, but not with clinical outcomes.

Immune checkpoint inhibitors have revolutionized the treatment landscape for patients with cancer. Multi-omics, including next-generation DNA and RNA sequencing, have enabled the identification of exploitable targets and the evaluation of immune mediator expression. There is one FDA-approved LAG-3 inhibitor and multiple in clinical trials for numerous cancers. We analyzed LAG-3 transcriptomic expression among 514 patients with diverse cancers, including 489 patients with clinical annotation for their advanced malignancies. Transcriptomic LAG-3 expression was highly variable between histologies/cancer types and within the same histology/cancer type. LAG-3 RNA levels correlated linearly, albeit weakly, with high RNA levels of other checkpoints, including PD-L1 (Pearson's R2 = 0.21 (P < 0.001)), PD-1 (R2 = 0.24 (P < 0.001)) and CTLA-4 (R2 = 0.19 (P < 0.001)); when examined for Spearman correlation, significance did not change. LAG-3 expression (dichotomized at ≥ 75th (high) versus < 75th (moderate/low) RNA percentile level) was not a prognostic factor for overall survival (OS) in 272 immunotherapy-naïve patients with advanced/metastatic disease (Kaplan Meier analysis; P = 0.54). High LAG-3 levels correlated with longer OS after anti-PD-1/PD-L1-based checkpoint blockade (univariate (P = 0.003), but not multivariate analysis (hazard ratio, 95% confidence interval = 0.80 (0.46-1.40) (P = 0.44))); correlation with longer progression-free survival showed a weak univariate trend (P = 0.13). Taken together, these results suggest that high LAG-3 levels in and of themselves do not predict resistance to anti-PD-1/PD-L1 checkpoint blockade. Even so, since LAG-3 is often co-expressed with PD-1, PD-L1 and/or CTLA-4, selecting patients for combinations of checkpoint blockade based on immunomic co-expression patterns is a strategy that merits exploration.

High indoleamine 2,3-dioxygenase transcript levels predict better outcome after front-line cancer immunotherapy.

Indoleamine 2,3-dioxygenase 1 (IDO1), which catabolizes tryptophan, is a potential target to unlock the immunosuppressive tumor microenvironment. Correlations between IDO1 and immune checkpoint inhibitor (ICI) efficacy remain unclear. Herein, we investigated IDO1 transcript expression across cancers and clinical outcome correlations. High IDO1 transcripts were more frequent in uterine (54.2%) and ovarian cancer (37.2%) but varied between and within malignancies. High IDO1 RNA expression was associated with high expression of PD-L1 (immune checkpoint ligand), CXCL10 (an effector T cell recruitment chemokine), and STAT1 (a component of the JAK-STAT pathway) (all multivariable p < 0.05). PIK3CA and CTCF alterations were more frequent in the high IDO1 group. High IDO1 expression was an independent predictor of progression-free survival (adjusted HR = 0.44, 95% CI 0.20-0.99, p = 0.049) and overall survival (adjusted HR = 0.31, 95% CI 0.11-0.87, p = 0.026) after front-line ICIs. IDO1 expression warrants further exploration as a predictive biomarker for immunotherapy. Moreover, co-expressed immunoregulatory molecules merit exploration for co-targeting.

The transcriptomic expression pattern of immune checkpoints shows heterogeneity between and within cancer types.

Transcriptomic expression profiles of immune checkpoint markers are of interest in order to decipher the mechanisms of immunotherapy response and resistance. Overall, 514 patients with various solid tumors were retrospectively analyzed in this study. The RNA expression levels of tumor checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) were ranked from 0-100 percentile based on a reference population. The expression of each checkpoint was correlated with cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) by immunohistochemistry (IHC). The cohort included 30 different tumor types, with colorectal cancer being the most common (27%). When RNA percentile rank values were categorized as "Low" (0-24), "Intermediate" (25-74), and "High" (75-100), each patient had a distinctive portfolio of the categorical expression of 16 checkpoint markers. Association between some checkpoint markers and cancer types were observed; NOS2 showed significantly higher expression in colorectal and stomach cancer (P < 0.001). Principal component analysis demonstrated no clear association between combined RNA expression patterns of 16 checkpoint markers and cancer types, TMB, MSI or PD-L1 IHC. Immune checkpoint RNA expression varies from patient to patient, both within and between tumor types, though colorectal and stomach cancer showed the highest levels of NOS2, a mediator of inflammation and immunosuppression. There were no specific combined expression patterns correlated with MSI, TMB or PD-L1 IHC. Next generation immunotherapy trials may benefit from individual analysis of patient tumors as selection criteria for specific immunomodulatory approaches.

Pan-cancer analysis of TIM-3 transcriptomic expression reveals high levels in pancreatic cancer and interpatient heterogeneity.

BACKGROUND: T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), an immune checkpoint receptor, dampens immune function. TIM-3 antagonists have entered the clinic. METHODS: We analyzed TIM-3 transcriptomic expression in 514 diverse cancers. Transcript abundance was normalized to internal housekeeping genes and ranked (0-100 percentile) to a reference population (735 tumors; 35 histologies [high≥75 percentile rank]). Ninety tumors (17.5%) demonstrated high TIM-3 expression. RESULTS: TIM-3 expression varied between and within tumor types. However, high TIM-3 expression was more common in pancreatic cancer (20/55 tumors, 36.4%; odds ratio, 95% confidence interval (pancreatic vs. other tumors) = 3.176 (1.733-5.818; p < 0.001, multivariate]). High TIM-3 also significantly and independently correlated with high PD-L1 (p = 0.014) and high CTLA-4 (p < 0.001) transcriptomic expression (multivariate). CONCLUSIONS: These observations indicate that TIM-3 RNA expression is heterogeneous, but more common in pancreatic cancer and in tumors exploiting PD-L1 and CTLA-4 checkpoints. Clinical trials with patient selection for matched immune-targeted combinations may be warranted.

Transcriptomic analysis of GITR and GITR ligand reveals cancer immune heterogeneity with implications for GITR targeting.

Glucocorticoid-induced tumor necrosis factor related protein (GITR) is a transmembrane protein expressed mostly on CD25+CD4+ regulatory T-cells (Tregs) and upregulated on all T-cells upon activation. It is a T-cell co-stimulatory receptor and has demonstrated promising anti-tumor activity in pre-clinical studies. To date, however, the efficacy of GITR agonism has been discouraging in clinical trials. This study explores GITR and GITR ligand (GITR-L) ribonucleic acid (RNA) expression in solid tumors in an attempt to delineate causes for variable responses to GITR agonists. RNA expression levels of 514 patients with a variety of cancer types were normalized to internal housekeeping gene profiles and ranked as percentiles. 99/514 patients (19.3%) had high GITR expression (defined as ≥ 75th percentile). Breast and lung cancer had the highest proportion of patients with high GITR expression (39% and 35%, respectively). The expression of concomitant high GITR and low-moderate GITR-L expression (defined as <75th percentile) was present in 31% and 30% of patients with breast and lung cancer respectively. High GITR expression also showed a significant independent association with high RNA expression of other immune modulator proteins, namely, PD-L1 immunohistochemistry (IHC) ≥1 (odds ratio (OR) 2.15, P=0.008), CTLA4 (OR=2.17, P=0.05) and OX40 high RNA expression (OR=2.64, P=0.001). Overall, these results suggest that breast and lung cancer have a high proportion of patients with a GITR and GITR-L RNA expression profile that merits further investigation in GITR agonism studies. The association of high GITR expression with high CTLA4 and OX40 RNA expression, as well as positive PD-L1 IHC, provides a rationale for a combination approach targeting these specific immune modulator proteins in patients whose tumors show such co-expression.

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.

Introduction: Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. Methods: We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. Results: We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. Discussion: These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.

Immunologic Factors Associated with Differential Response to Neoadjuvant Chemoimmunotherapy in Triple-Negative Breast Cancer.

Background: KEYNOTE-522 resulted in FDA approval of the immune checkpoint inhibitor pembrolizumab in combination with neoadjuvant chemotherapy for patients with early-stage, high-risk, triple-negative breast cancer (TNBC). Unfortunately, pembrolizumab is associated with several immune-related adverse events (irAEs). We aimed to identify potential tumor microenvironment (TME) biomarkers which could predict patients who may attain pathological complete response (pCR) with chemotherapy alone and be spared the use of anti-PD-1 immunotherapy. Methods: Comprehensive immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on matched FFPE tumor samples from 22 stage I-III TNBC patients (14 patients treated with neoadjuvant chemotherapy alone (NAC) and 8 treated with neoadjuvant chemotherapy combined with pembrolizumab (NAC+I)). Results: Differential gene expression analysis revealed that in the NAC group, IL12B and IL13 were both significantly associated with pCR. In the NAC+I group, LCK and TP63 were significantly associated with pCR. Patients in both treatment groups exhibiting pCR tended to have greater tumor inflammation than non-pCR patients. In the NAC+I group, patients with pCR tended to have greater cell proliferation and higher PD-L1 expression, while in the NAC group, patients with pCR tended to have lower cancer testis antigen expression. Additionally, the NAC+I group trended toward a lower relative dose intensity averaged across all chemotherapy drugs, suggesting that more dose reductions or treatment delays occurred in the NAC+I group than the NAC group. Conclusions: A comprehensive understanding of immunologic factors could potentially predict pCR to chemotherapy alone, enabling the avoidance of the unnecessary treatment of these patients with checkpoint inhibitors.

The Impact of Prior Single-Gene Testing on Comprehensive Genomic Profiling Results for Patients with Non-Small Cell Lung Cancer.

INTRODUCTION: Tissue-based broad molecular profiling of guideline-recommended biomarkers is advised for the therapeutic management of patients with non-small cell lung cancer (NSCLC). However, practice variation can affect whether all indicated biomarkers are tested. We aimed to evaluate the impact of common single-gene testing (SGT) on subsequent comprehensive genomic profiling (CGP) test outcomes and results in NSCLC. METHODS: Oncologists who ordered SGT for guideline-recommended biomarkers in NSCLC patients were prospectively contacted (May-December 2022) and offered CGP (DNA and RNA sequencing), either following receipt of negative SGT findings, or instead of SGT for each patient. We describe SGT patterns and compare CGP completion rates, turnaround time, and recommended biomarker detection for NSCLC patients with and without prior negative SGT results. RESULTS: Oncologists in > 80 community practices ordered CGP for 561 NSCLC patients; 135 patients (27%) first had negative results from 30 different SGT combinations; 84% included ALK, EGFR and PD-L1, while only 3% of orders included all available SGTs for guideline-recommended genes. Among patients with negative SGT results, CGP was attempted using the same tissue specimen 90% of the time. There were also significantly more CGP order cancellations due to tissue insufficiency (17% vs. 7%), DNA sequencing failures (13% vs. 8%), and turnaround time > 14 days (62% vs. 29%) than among patients who only had CGP. Forty-six percent of patients with negative prior SGT had positive CGP results for recommended biomarkers, including targetable genomic variants in genes beyond ALK and EGFR, such as ERBB2, KRAS (non-G12C), MET (exon 14 skipping), NTRK2/3, and RET . CONCLUSION: For patients with NSCLC, initial use of SGT increases subsequent CGP test cancellations, turnaround time, and the likelihood of incomplete molecular profiling for guideline-recommended biomarkers due to tissue insufficiency.

Patients with non-small cell lung cancer (NSCLC) should have their tumor tissue tested for all recommended biomarkers that can help identify their best treatment options. Traditional tests look at gene biomarkers one by one (single-gene testing), and doctors can order some or all these tests individually or in a group. However, some recommended biomarkers cannot be tested by traditional single-gene tests at all. Newer technology (next-generation sequencing) covers all current recommended treatment biomarkers in one test (comprehensive genomic profiling), but this testing is more expensive and can take more time. Our study shows that NSCLC patients do not get all recommended treatment biomarkers tested when a single-gene testing approach is taken. Single-gene testing also used up some patients' tumor tissue entirely, such that further testing by comprehensive genomic profiling could not be done at all (17% vs. 7% for patients with no prior single-gene tests), resulted in more sequencing failures (13% vs. 8%), and had turnaround time for results greater than 14 days for more patients (62% vs. 29%). When comprehensive genomic profiling was completed, 46% of patients with negative results from prior single-gene testing had positive results for recommended treatment biomarkers that were not included in the initial single-gene tests. To ensure that NSCLC patients receive testing for all recommended biomarkers, comprehensive genomic profiling must be performed first.

Comprehensive Assessment of Immune Phenotype and Its Effects on Survival Outcomes in HER2-Low versus HER2-Zero Breast Cancer.

Background: The understanding of molecular characteristics of HER2-low breast cancer is evolving since the establishment of trastuzumab deruxtecan. Here, we explore the differences in expression patterns of immune-related genes in the tumor immune microenvironment (TME) and survival between HER2-low and HER2-zero breast cancers. Methods: Comprehensive genomic and immune profiling, including RNA-seq gene expression assessment of 395 immune genes, was performed on FFPE samples from 129 patients with advanced HER2-negative (immunohistochemistry (IHC) 0, 1+ or 2+ with negative ERBB2 amplification by in-situ hybridization) breast cancer. Both estrogen receptor (ER) and HER2 statuses were obtained from available pathology reports. mRNA expressions of immune biomarkers, except for PD-L1 IHC and TMB, were derived from RNA-seq. Statistical comparisons were performed using the Kruskal-Wallis or Wilcoxon Rank-Sum test or the two-sample test for equality of proportions with continuity correction (p≤0.05 for significance). Survival differences were calculated using Kaplan-Meier analysis (p≤0.05 for significance). Results: There were no significant differences in mRNA expressions of immune-related genes between HER2-low and HER2-zero breast cancers. However, HER2-low breast cancers were associated with a higher proportion of ER-positivity. When ER was analyzed along with HER2, we observed a significantly higher tumor immunogenic signature (TIGS) expression in HER2-zero/ER-negative tumors than in HER2-low/ER-positive tumors (p=0.0088). Similarly, lower expression of PD-L1 and T cell immunoglobulin and ITIM domain (TIGIT) mRNA was observed in HER2-low/ER-positive tumors when compared to HER2-zero/ER-negative tumors (p=0.014 and 0.012, respectively). Patients with HER2-low tumors had a longer median OS than those with HER2-zero tumors (94 months vs 42 months, p=0.0044). Conclusion: Patients with HER2-low breast cancer have longer survivals yet display no differences in immune-related gene expression when compared to those with HER2-zero cancers. The differences in survival can be attributed to the higher rate of ER-positivity seen in HER2-low breast cancers, compared to HER2-zero tumors.

Cancer immunity marker RNA expression levels across gynecologic cancers: Implications for immunotherapy.

Background: Our objective was to characterize cancer immunity marker expression in gynecologic cancers and compare immune landscapes between gynecologic tumor subtypes and with non-gynecologic solid tumors. Methods: RNA expression levels of 51 cancer-immunity markers were analyzed in patients with gynecologic cancers vs. non-gynecologic cancers, and normalized to a reference population of 735 control cancers, ranked from 0-100, and categorized as low (0-24), moderate (25-74), or high (75-100) percentile rank. Results: Of the 72 patients studied, 43 (60%) had ovarian, 24 (33%) uterine, and 5 (7%) cervical cancer. No two immune profiles were identical according to expression rank (0-100) or rank level (low, moderate, or high). Patients with cervical cancer had significantly higher expression level ranks of immune activating, pro-inflammatory, tumor infiltrating lymphocyte markers and checkpoints than patients with uterine or ovarian cancer (p<0.001 for all comparisons). However, there were no significant differences in immune marker expression between uterine and ovarian cancers. Tumors with PD-L1 TPS =>1% versus 0% had significantly higher expression levels of pro-inflammatory markers (58 vs. 49%, p=0.0004). Compared to patients with non-gynecologic cancers, more patients with gynecologic cancers express high levels of IDO-1 (44 vs. 13%, p<0.001), LAG3 (35 vs. 21%, p=0.008) and IL10 (31 vs. 15%, p=0.002.) Conclusions: Patients with gynecologic cancers have complex and heterogeneous immune landscapes that are distinct from patient to patient and from other solid tumors. High levels of IDO1 and LAG3 suggest that clinical trials with IDO1 inhibitors or LAG3 inhibitors, respectively, may be warranted in gynecologic cancers.

PD-L1 Expression by RNA-Sequencing in Non-Small Cell Lung Cancer: Concordance with Immunohistochemistry and Associations with Pembrolizumab Treatment Outcomes.

Programmed cell death ligand (PD-L1) expression by immunohistochemistry (IHC) lacks sensitivity for pembrolizumab immunotherapy selection in non-small cell lung cancer (NSCLC), particularly for tumors with low expression. We retrospectively evaluated transcriptomic PD-L1 by mRNA next-generation sequencing (RNA-seq). In an unselected NSCLC patient cohort (n = 3168) tested during standard care (2017-2021), PD-L1 IHC and RNA-seq demonstrated moderate concordance, with 80% agreement overall. Most discordant cases were either low or negative for PD-L1 expression by IHC but high by RNA-seq. RNA-seq accurately discriminated PD-L1 IHC high from low tumors by receiver operator curve (ROC) analysis but could not distinguish PD-L1 IHC low from negative tumors. In a separate pembrolizumab monotherapy cohort (n = 102), NSCLC tumors classified as PD-L1 high versus not high by RNA-seq had significantly improved response, progression-free survival, and overall survival as an individual measure and in combination with IHC high or low status. PD-L1 IHC status (high or low) trended toward but had no significant associations with improved outcomes. Conventional PD-L1 IHC testing has inherent limitations, making it an imperfect reference standard for evaluating novel testing technologies. RNA-seq offers an objective PD-L1 measure that could represent a complementary method to IHC to improve NSCLC patient selection for immunotherapy.

T-cell priming transcriptomic markers: implications of immunome heterogeneity for precision immunotherapy.

Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.