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Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000 TM sequencing run with a turnaround time of <7 days from specimen receipt to report. The results demonstrate that the scalable assay accurately and reproducibly detects small variants, copy number alterations, microsatellite instability (MSI) and tumor mutational burden (TMB) from 40ng DNA, and multiple gene fusions, including known and unknown partners and splice variants from 20ng RNA. 717 tumor samples and reference materials with previously known alterations in 96 cancer-related genes were sequenced to evaluate assay performance. All variant classes were reliably detected at consistent and reportable variant allele percentages with >99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Background Lymphocyte activation gene 3 (LAG‐3) or CD223 is a transmembrane protein that serves as an immune checkpoint which attenuates T‐cell activation. Many clinical trials of LAG‐3 inhibitors have had modest effects, but recent data indicate that the LAG‐3 antibody relatlimab, together with nivolumab (anti‐PD‐1), provided greater benefit than nivolumab alone in patients with melanoma. Methods In this study, the RNA expression levels of 397 genes were assessed in 514 diverse cancers at a clinical‐grade laboratory (OmniSeq: https://www.omniseq.com/). Transcript abundance was normalized to internal housekeeping gene profiles and ranked (0–100 percentile) using a reference population (735 tumors; 35 histologies). Results A total of 116 of 514 tumors (22.6%) had high LAG‐3 transcript expression (≥75 percentile rank). Cancers with the greatest proportion of high LAG‐3 transcripts were neuroendocrine (47% of patients) and uterine (42%); colorectal had among the lowest proportion of high LAG‐3 expression (15% of patients) (all p < 0.05 multivariate); 50% of melanomas were high LAG‐3 expressors. There was significant independent association between high LAG‐3 expression and high expression of other checkpoints, including programmed death‐ligand 1 (PD‐L1), PD‐1, and CTLA‐4, as well as high tumor mutational burden (TMB) ≥10 mutations/megabase, a marker for immunotherapy response (all p < 0.05 multivariate). However, within all tumor types, there was inter‐patient variability in LAG‐3 expression level. Conclusions Prospective studies are therefore needed to determine if high levels of the LAG‐3 checkpoint are responsible for resistance to anti‐PD‐1/PD‐L1 or anti‐CTLA‐4 antibodies. Furthermore, a precision/personalized immunotherapy approach may require interrogating individual tumor immunograms to match patients to the right combination of immunotherapeutic agents for their malignancy.

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. Plain language summary 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.

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.

Background: Inducible T-cell co-stimulator (ICOS) and its ligand (ICOSL) form a complex, two-faced immune machinery that can lead to both immune stimulation and inhibition. Objective: We explored ICOS transcriptomic expression patterns and their relationship with other checkpoints and with outcomes in patients with advanced/metastatic cancers. Design: This was a retrospective cohort study. Methods: RNA expression for ICOS and other immune checkpoints was quantified by RNA sequencing and stratified by rank values into high (75–100 percentiles) and low (0–24 percentiles). Fischer’s exact tests were used for univariate analyses to evaluate independent predictors of ICOS high and logistic regression was used for multivariate analyses. Progression-free survival (PFS) and overall survival (OS) for ICOS high versus not high expression were evaluated using the log-rank test (Kaplan–Meier analysis) and Cox proportional hazards. Results: High ICOS (⩾75 percentile RNA rank) was present in 14% of 514 cancers and independently associated with high PD-1 (p = 0.025), PD-L1 (p < 0.0001), and CTLA-4 RNA expression (p < 0.0001) and with patients not having colorectal cancer (p = 0.0009; multivariate analysis). Patterns of ICOS and ICOSL expression varied between and within tumor types. For 217 patients receiving immune checkpoint inhibitors (ICIs), there were no significant differences in PFS or OS between patients with ICOS high versus not-high expression (multivariate analysis). In 272 immunotherapy-naïve patients, OS was also similar between patients with ICOS high versus not-high expression (p = 0.91). Conclusion: High ICOS expression was not a prognostic marker and did not independently predict outcomes after ICIs. Variable expression of ICOS/ICOSL between tumors and association of high ICOS with high PD-1, PD-L1, and CTLA-4 suggest that individual tumor immunomic analysis may be required for optimized patient selection in clinical trials targeting the ICOS/ICOSL system, especially when given in combination with ICIs. Trial registration: UCSD_PREDICT, NCT02478931.

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.

Background ICOS (inducible T‐cell co‐stimulator) and ICOS ligand (ICOSL) are part of an important, complex pathway that can lead to both immune stimulation and suppression. ICOS and ICOSL have heterogeneous expression patterns between and within tumor types. Methods This review provides an overview of ICOS and ICOSL, their mechanisms of action, expression in cancer and other diseases, and clinical trials exploring therapies targeting ICOS. Results Because of the bidirectional immune impact of the ICOS/ICOSL signaling pathway, both ICOS agonists and antagonists are under development and evaluation in clinical trials. The majority of clinical trials have focused on the development of ICOS agonists, with only one study exploring an ICOS antagonist; there have been no clinical trials developing ICOSL agonists or antagonists in oncology. ICOS can be expressed on immune‐activating effector T‐cell and immunosuppressive regulatory T‐cell (Tregs). Thus, it is critical to determine where and how ICOS is expressed in order to evaluate the role for agonists versus antagonists. To date, ICOS agonists have shown limited activity in patients with malignancies, perhaps because of the lack of biomarker‐based trials. However, an ICOS antagonist demonstrated a 44% response rate in angioimmunoblastic T‐cell lymphoma; ICOS is highly expressed on T‐follicular helper cells (type of CD4 cell) and proliferation of these cells may be a pathogenic mechanism for these lymphomas. A role for the ICOS/ICOSL signaling pathway has also been implicated outside of oncology, including in viral infections such as COVID‐19, and in autoimmune conditions such as asthma and systemic lupus erythematosus. Conclusion Biomarker‐driven approaches will be important to individualize therapy and ascertain which cancer patients will derive the greatest benefit from ICOS‐directed combination therapy approaches. ICOS (inducible T‐cell co‐stimulator) and ICOS ligand (ICOSL) are part of an important, complex pathway that can lead to both immune stimulation and suppression. Both ICOS agonists and antagonists are under development as oncology therapeutics and biomarker driven approaches will be important to ascertain which patients will derive the greatest benefit these therapies.

Using complete genome analysis, we sequenced five bladder tumors accrued from patients with muscle-invasive transitional cell carcinoma of the urinary bladder (TCC-UB) and identified a spectrum of genomic aberrations. In three tumors, complex genotype changes were noted. All three had tumor protein p53 mutations and a relatively large number of single-nucleotide variants (SNVs; average of 11.2 per megabase), structural variants (SVs; average of 46), or both. This group was best characterized by chromothripsis and the presence of subclonal populations of neoplastic cells or intratumoral mutational heterogeneity. Here, we provide evidence that the process of chromothripsis in TCC-UB is mediated by nonhomologous end-joining using kilobase, rather than megabase, fragments of DNA, which we refer to as “stitchers,” to repair this process. We postulate that a potential unifying theme among tumors with the more complex genotype group is a defective replication–licensing complex. A second group (two bladder tumors) had no chromothripsis, and a simpler genotype, WT tumor protein p53, had relatively few SNVs (average of 5.9 per megabase) and only a single SV. There was no evidence of a subclonal population of neoplastic cells. In this group, we used a preclinical model of bladder carcinoma cell lines to study a unique SV (translocation and amplification) of the gene glutamate receptor ionotropic N-methyl D-aspertate as a potential new therapeutic target in bladder cancer.

Programmed cell death protein 1 (PD-1) is a critical immune checkpoint receptor and a target for cancer immune checkpoint inhibitors (ICI). We investigated PD-1 transcript expression across cancer types and its correlations to clinical outcomes. Using a reference population, PD-1 expression was calculated as percentiles in 489 of 514 patients (31 cancer types) with advanced/metastatic disease. PD-1 RNA expression varied across and within cancer types; pancreatic and liver/bile duct malignancies displayed the highest rates of high PD-1 (21.82% and 21.05%, respectively). Elevated CTLA-4, LAG-3, and TIGIT RNA expression were independently correlated with high PD-1. Although high PD-1 was not associated with outcome in immunotherapy-naïve patients (n = 272), in patients who received ICIs (n = 217), high PD-1 transcript expression was independently correlated with prolonged survival (hazard ratio 0.40; 95%CI, 0.18–0.92). This study identifies PD-1 as an important biomarker in predicting ICI outcomes, and advocates for comprehensive immunogenomic profiling in cancer management.

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.