The Different Immune Profiles of Normal Colonic Mucosa in Cancer-Free Lynch Syndrome Carriers and Lynch Syndrome Colorectal Cancer Patients.

BACKGROUND & AIMS: Owing to the high load of immunogenic frameshift neoantigens, tumors arising in individuals with Lynch syndrome (LS), the most common inherited colorectal cancer (CRC) syndrome, are characterized by a pronounced immune infiltration. However, the immune status of normal colorectal mucosa in LS is not well characterized. We assessed the immune infiltrate in tumor-distant normal colorectal mucosa from LS CRC patients, sporadic microsatellite-unstable (MSI) and microsatellite-stable (MSS) CRC patients, and cancer-free LS carriers. METHODS: CD3-positive, FOXP3-positive, and CD8-positive T cells were quantified in, respectively, 219, 233, and 201 formalin-fixed paraffin-embedded (FFPE) normal colonic mucosa tissue sections from CRC patients and cancer-free LS carriers and 26, 22, and 19 LS CRCs. CD3-positive T cells were also quantified in an independent cohort of 97 FFPE normal rectal mucosa tissue sections from LS carriers enrolled in the CAPP2 clinical trial. The expression of 770 immune-relevant genes was analyzed in a subset of samples with the use of the NanoString nCounter platform. RESULTS: LS normal mucosa specimens showed significantly elevated CD3-, FOXP3-, and CD8-positive T-cell densities compared with non-LS control specimens. Gene expression profiling and cluster analysis revealed distinct immune profiles in LS carrier mucosa with and without cancer manifestation. Long-term follow-up of LS carriers within the CAPP2 trial found a correlation between mucosal T-cell infiltrate and time to subsequent tumor occurrence. CONCLUSIONS: LS carriers show elevated mucosal T-cell infiltration even in the absence of cancer. The normal mucosa immune profile may be a temporary or permanent tumor risk modifier in LS carriers.

Deciphering the immunosuppressive tumor microenvironment in ALK- and EGFR-positive lung adenocarcinoma.

INTRODUCTION: The advent of immune checkpoint blockade (ICB) has led to significantly improved disease outcome in lung adenocarcinoma (ADC), but response of ALK/EGFR-positive tumors to immune therapy is limited. The underlying immune biology is incompletely understood. METHODS: We performed comparative mRNA expression profiling of 31 ALK-positive, 40 EGFR-positive and 43 ALK/EGFR-negative lung ADC focused on immune gene expression. The presence and levels of tumor infiltration lymphocytes (TILs) as well as fourteen specific immune cell populations were estimated from the gene expression profiles. RESULTS: While total TILs were not lower in ALK-positive and EGFR-positive tumors compared to ALK/EGFR-negative tumors, specific immunosuppressive characteristics were detected in both subgroups: In ALK-positive tumors, regulatory T cells were significantly higher compared to EGFR-positive (fold change: FC = 1.9, p = 0.0013) and ALK/EGFR-negative tumors (FC = 2.1, p = 0.00047). In EGFR-positive tumors, cytotoxic cells were significantly lower compared to ALK-positive (FC = - 1.7, p = 0.016) and to ALK/EGFR-negative tumors (FC = - 2.1, p = 2.0E-05). A total number of 289 genes, 40 part of cytokine-cytokine receptor signaling, were differentially expressed between the three subgroups. Among the latter, five genes were differently expressed in both ALK-positive and EGFR-positive tumors, while twelve genes showed differential expression solely in ALK-positive tumors and eleven genes solely in EGFR-positive tumors. CONCLUSION: Targeted gene expression profiling is a promising tool to read out tumor microenvironment characteristics from routine diagnostic lung cancer biopsies. Significant immune reactivity including specific immunosuppressive characteristics in ALK- and EGFR-positive lung ADC, but not a total absence of immune infiltration supports further clinical evaluation of immune-modulators as partners of ICB in such tumors.

Decoding and targeting the molecular basis of MACC1-driven metastatic spread: Lessons from big data mining and clinical-experimental approaches.

Metastasis remains the key issue impacting cancer patient survival and failure or success of cancer therapies. Metastatic spread is a complex process including dissemination of single cells or collective cell migration, penetration of the blood or lymphatic vessels and seeding at a distant organ site. Hundreds of genes involved in metastasis have been identified in studies across numerous cancer types. Here, we analyzed how the metastasis-associated gene MACC1 cooperates with other genes in metastatic spread and how these coactions could be exploited by combination therapies: We performed (i) a MACC1 correlation analysis across 33 cancer types in the mRNA expression data of TCGA and (ii) a comprehensive literature search on reported MACC1 combinations and regulation mechanisms. The key genes MET, HGF and MMP7 reported together with MACC1 showed significant positive correlations with MACC1 in more than half of the cancer types included in the big data analysis. However, ten other genes also reported together with MACC1 in the literature showed significant positive correlations with MACC1 in only a minority of 5 to 15 cancer types. To uncover transcriptional regulation mechanisms that are activated simultaneously with MACC1, we isolated pan-cancer consensus lists of 1306 positively and 590 negatively MACC1-correlating genes from the TCGA data and analyzed each of these lists for sharing transcription factor binding motifs in the promotor region. In these lists, binding sites for the transcription factors TELF1, ETS2, ETV4, TEAD1, FOXO4, NFE2L1, ELK1, SP1 and NFE2L2 were significantly enriched, but none of them except SP1 was reported in combination with MACC1 in the literature. Thus, while some of the results of the big data analysis were in line with the reported experimental results, hypotheses on new genes involved in MACC1-driven metastasis formation could be generated and warrant experimental validation. Furthermore, the results of the big data analysis can help to prioritize cancer types for experimental studies and testing of combination therapies.

Leveraging Off-Target Reads in Panel Sequencing for Homologous Recombination Repair Deficiency Screening in Tumor.

Targeted tumor only sequencing has become a standard practice in cancer diagnostics. This study aims to develop an approach for robust copy number variant calling in tumor samples using only off-target region (OTR) reads. We also established a clinical use case for homologous recombination deficiency (HRD) score estimation (HRDest) using the sum of telomeric-allelic imbalance and large-scale state transition scores without the need for loss of heterozygosity information. A strong correlation was found between HRD score and the sum of telomeric-allelic imbalance + large-scale state transition in The Cancer Genome Atlas cohort (ρ = 0.99, P < 2.2 × 10-16) and in a clinical in-house cohort of 34 tumors (ρ = 0.9, P = 5.1 × 10-13) comparing whole-exome sequencing and targeted sequencing data. HRDest scores from 1086 clinical cases were compared with The Cancer Genome Atlas data set. There were no significant differences in HRD score distribution within the analyzed tumor types. As a control, commercially available HRD standards were also sequenced, and the HRDest scores obtained from the OTR reads were well within the HRD reference range provided by the manufacturer. In conclusion, OTR reads of tumor-only panel sequencing can be used to determine genome-wide copy number variant profiles and to approximate HRD scores.

Genomic heterogeneity at baseline is associated with T790M resistance mutations in EGFR-mutated lung cancer treated with the first-/second-generation tyrosine kinase inhibitors.

This study analyzed whether extended molecular profiling can predict the development of epidermal growth factor receptor (EGFR) gene T790M mutation, which is the most frequent resistance alteration in non-small cell lung cancer (NSCLC) after treatment with the first-/second-generation (1G/2G) EGFR inhibitors (tyrosine kinase inhibitors [TKIs]), but only weakly associated with clinical characteristics. Whole exome sequencing (WES) was performed on pretreatment tumor tissue with matched normal samples from NSCLC patients with (n = 25, detected in tissue or blood rebiopsies) or without (n = 14, negative tissue rebiopsies only) subsequent EGFR p.T790M mutation after treatment with 1G/2G EGFR TKI. Several complex genetic biomarkers were assessed using bioinformatic methods. After treatment with first-line afatinib (44%) or erlotinib/gefitinib (56%), median progression-free survival and overall survival were 12.1 and 33.7 months, respectively. Clinical and tumor genetic characteristics, including age (median, 66 years), sex (74% female), smoking (69% never/light smokers), EGFR mutation type (72% exon 19 deletions), and TP53 mutations (41%) were not significantly associated with T790M mutation (p > 0.05). By contrast, complex biomarkers including tumor mutational burden, the clock-like mutation signature SBS1 + 5, tumor ploidy, and markers of subclonality including mutant-allele tumor heterogeneity, subclonal copy number changes, and median tumor-adjusted variant allele frequency were significantly higher at baseline in tumors with subsequent T790M mutation (all p < 0.05). Each marker alone could predict subsequent development of T790M with an area under the curve (AUC) of 0.72-0.77, but the small number of cases did not allow confirmation of better performance for biomarker combinations in leave-one-out cross-validated logistic regression (AUC 0.69, 95% confidence interval: 0.50-0.87). Extended molecular profiling with WES at initial diagnosis reveals several complex biomarkers associated with subsequent development of T790M resistance mutation in NSCLC patients receiving first-/second-generation TKIs as the first-line therapy. Larger prospective studies will be necessary to define a forecasting model.

Homogenous TP53mut-associated tumor biology across mutation and cancer types revealed by transcriptome analysis.

TP53 is the most frequently mutated gene in human cancer. While no TP53-targeting drugs have been approved in the USA or Europe so far, preclinical and clinical studies are underway to investigate targeting of specific or all TP53 mutations, for example, by restoration of the functionality of mutated TP53 (TP53mut) or protecting wildtype TP53 (TP53wt) from negative regulation. We performed a comprehensive mRNA expression analysis in 24 cancer types of TCGA to extract (i) a consensus expression signature shared across TP53 mutation types and cancer types, (ii) differential gene expression patterns between tumors harboring different TP53 mutation types such as loss of function, gain of function or dominant-negative mutations, and (iii) cancer-type-specific patterns of gene expression and immune infiltration. Analysis of mutational hotspots revealed both similarities across cancer types and cancer type-specific hotspots. Underlying ubiquitous and cancer type-specific mutational processes with the associated mutational signatures contributed to explaining this observation. Virtually no genes were differentially expressed between tumors harboring different TP53 mutation types, while hundreds of genes were over- and underexpressed in TP53mut compared to TP53wt tumors. A consensus list included 178 genes that were overexpressed and 32 genes that were underexpressed in the TP53mut tumors of at least 16 of the investigated 24 cancer types. In an association analysis of immune infiltration with TP53 mutations in 32 cancer subtypes, decreased immune infiltration was observed in six subtypes, increased infiltration in two subtypes, a mixed pattern of decreased and increased immune cell populations in four subtypes, while immune infiltration was not associated with TP53 status in 20 subtypes. The analysis of a large cohort of human tumors complements results from experimental studies and supports the view that TP53 mutations should be further evaluated as predictive markers for immunotherapy and targeted therapies.

Accurate tumor purity determination is critical for the analysis of homologous recombination deficiency (HRD).

Homologous recombination deficiency (HRD) is a predictive marker for response to poly (ADP-ribose) polymerase inhibitors (PARPi) in ovarian carcinoma. HRD scores have entered routine diagnostics, but the influence of algorithms, parameters and confounders has not been analyzed comprehensively. A series of 100 poorly differentiated ovarian carcinoma samples was analyzed using whole exome sequencing (WES) and genotyping. Tumor purity was determined using conventional pathology, digital pathology, and two bioinformatic methods. HRD scores were calculated from copy number profiles determined by Sequenza and by Sclust either with or without fixed tumor purity. Tumor purity determination by digital pathology combined with a tumory purity informed variant of Sequenza served as reference method for HRD scoring. Seven tumors had deleterious mutations in BRCA1/2, 12 tumors had deleterious mutations in other homologous recombination repair (HRR) genes, 18 tumors had variants of unknown significance (VUS) in BRCA1/2 or other HRR genes, while the remaining 63 tumors had no relevant alterations. Using the reference method for HRD scoring, 68 tumors were HRD-positive. HRDsum determined by WES correlated strongly with HRDsum determined by single nucleotide polymorphism (SNP) arrays (R = 0.85). Conventional pathology systematically overestimated tumor purity by 8% compared to digital pathology. All investigated methods agreed on classifying the deleterious BRCA1/2-mutated tumors as HRD-positive, but discrepancies were observed for some of the remaining tumors. Discordant HRD classification of 11% of the tumors was observed comparing the tumor purity uninformed default of Sequenza and the reference method. In conclusion, tumor purity is a critical factor for the determination of HRD scores. Assistance by digital pathology helps to improve accuracy and imprecision of its estimation.

Spatial profiling of the microenvironment reveals low intratumoral heterogeneity and STK11-associated immune evasion in therapy-naïve lung adenocarcinomas.

OBJECTIVE: Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting. MATERIALS AND METHODS: We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype). For each sample the expression of 770 immunooncology-related genes was analyzed using the nCounter platform, while the mutational status was determined by hybrid capture-based next-generation sequencing (NGS) using a large panel covering more than 500 genes. RESULTS: Global unsupervised analyses revealed clustering of the samples into two groups corresponding to a 'hot' or 'cold' immunologic tumor contexture based on the abundance of immune cell infiltrates. All analyzed specific immune cell signatures (ICsig) showed a significantly higher intertumoral than intratumoral heterogeneity (p < 0.02), as most of the analyzed cases (14/19) showed a very homogenous spatial immune cell profile. PD-L1 exhibited a significantly higher intertumoral than intratumoral heterogeneity (p = 1.03e-13). We found a specific association with 'cold' TME for STK11 (11/14, p < 0.07), but not KRAS, TP53, LRP1B, MTOR, U2AF1 co-mutations, and validated this finding using The Cancer Genome Atlas (TCGA) data. CONCLUSION: Early-stage lung adenocarcinomas show considerable intertumoral, but limited intratumoral heterogeneity, which is clinically highly relevant as assessment before neoadjuvant treatment is based on small biopsies. STK11 mutations are specifically associated with a 'cold' TME, which could affect the efficacy of perioperative immunotherapy.

Nivolumab and ipilimumab in recurrent or refractory cancer of unknown primary: a phase II trial.

Cancer of unknown primary has a dismal prognosis, especially following failure of platinum-based chemotherapy. 10-20% of patients have a high tumor mutational burden (TMB), which predicts response to immunotherapy in many cancer types. In this prospective, non-randomized, open-label, multicenter Phase II trial (EudraCT 2018-004562-33; NCT04131621), patients relapsed or refractory after platinum-based chemotherapy received nivolumab and ipilimumab following TMBhigh vs. TMBlow stratification. Progression-free survival (PFS) represented the primary endpoint; overall survival (OS), response rates, duration of clinical benefit and safety were the secondary endpoints. The trial was prematurely terminated in March 2021 before reaching the preplanned sample size (n = 194). Among 31 evaluable patients, 16% had a high TMB ( > 12 mutations/Mb). Overall response rate was 16% (95% CI 6-34%), with 7.7% (95% CI 1-25%) vs. 60% (95% CI 15-95%) in TMBlow and TMBhigh, respectively. Although the primary endpoint was not met, high TMB was associated with better median PFS (18.3 vs. 2.4 months) and OS (18.3 vs. 3.6 months). Severe immune-related adverse events were reported in 29% of cases. Assessing on-treatment dynamics of circulating tumor DNA using combined targeted hotspot mutation and shallow whole genome sequencing as part of a predefined exploratory analysis identified patients benefiting from immunotherapy irrespective of initial radiologic response.

Analysis of rare fusions in NSCLC: Genomic architecture and clinical implications.

OBJECTIVES: Molecular diagnosis for targeted therapies has been improved significantly in non-small-cell lung cancer (NSCLC) patients in recent years. Here we report on the prevalence of rare fusions in NSCLC and dissect their genomic architecture and potential clinical implications. MATERIALS AND METHODS: Overall, n = 5554 NSCLC patients underwent next-generation sequencing (NGS) for combined detection of oncogenic mutations and fusions either at primary diagnosis (n = 5246) or after therapy resistance (n = 308). Panels of different sizes were employed with closed amplicon-based, or open assays, i.e. anchored multiplex PCR (AMP) and hybrid capture-based, for detection of translocations, including "rare" fusions, defined as those beyond ALK, ROS1, RET and <0.5 % frequency in NSCLC. RESULTS: Rare fusions involving EGFR, MET, HER2, BRAF and other potentially actionable oncogenes were detected in 0.5% (n = 26) of therapy-naive and 2% (n = 6) TKI-treated tumors. Detection was increased using open assays and/or larger panels, especially those covering >25 genes, by approximately 1-2% (p = 0.001 for both). Patient characteristics (age, gender, smoking, TP53 co-mutations (56%), or mean tumor mutational burden (TMB) (4.8 mut/Mb)) showed no association with presence of rare fusions. Non-functional alterations, i.e. out-of-frame or lacking kinase domains, comprised one-third of detected rare fusions and were significantly associated with simultaneous presence of classical oncogenic drivers, e.g. EGFR or KRAS mutations (p < 0.001), or use of larger panels (frequency of non-functional among the detected rare fusions 57% for 25+ gene- vs. 12% for smaller panels, p < 0.001). As many rare fusions were identified before availability of targeted therapy, mean survival for therapy-naïve patients was 23.8 months, comparable with wild-type tumors. CONCLUSION: Approximately 1-2% of advanced NSCLC harbor rare fusions, which are potentially actionable and may support diagnosis. Routine adoption of broad NGS assays capable to identify exact fusion points and potentially retained protein domains can increase the yield of therapeutically relevant molecular information in advanced NSCLC.

Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients.

A growing number of druggable targets and national initiatives for precision oncology necessitate broad genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a positive percentage agreement (PPA) between 91 and 95% and a positive predictive value (PPV) between 82 and 95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Explanations for deviations included low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

Homologous recombination deficiency is inversely correlated with microsatellite instability and identifies immunologically cold tumors in most cancer types.

Homologous recombination deficiency (HRD) leads to DNA double-strand breaks and can be exploited by the use of poly (ADP-ribose) polymerase (PARP) inhibitors to induce synthetic lethality. Extending the original therapeutic concept, the role of HRD is currently being investigated in clinical trials testing immune checkpoint blockers alone or in combination with PARP inhibitors, but the relationship between HRD and immune cell context in cancer is incompletely understood. We analyzed the association between immune cell composition, gene expression, and HRD in 9,041 tumors of 32 solid cancer types from The Cancer Genome Atlas (TCGA). The numbers of genomic scars were quantified by the HRD sum score (HRDsum) including loss of heterozygosity, large-scale state transitions, and telomeric allelic imbalance. The T-cell inflamed gene expression profile correlated weakly, but significantly positively, with HRDsum across cancer types (ρ = 0.17). Within individual cancer types, a significantly positive correlation was observed only in breast cancer, ovarian cancer, and four other cancer types, but not in the remaining 26 cancer types. HRDsum and tumor mutational burden (TMB) correlated significantly positively across cancer types (ρ = 0.42) and within 18 cancer types. HRDsum and a proliferation metagene correlated significantly positively across cancer types (ρ = 0.52) and within 20 cancer types. Mismatch repair deficiency and HRD as well as proofreading deficiency showed a high level of exclusivity. High HRD scores were associated with an immunologically activated tumor microenvironment only in a minority of cancer types. Our data favor the combination of genetic markers, complex genomic markers (including HRDsum and TMB), and other molecular markers (including proliferation scores) for a precise and comprehensive read-out of the tumor biology and an individually tailored treatment.

The impact of TP53 co-mutations and immunologic microenvironment on outcome of lung cancer with EGFR exon 20 insertions.

BACKGROUND: EGFR exon20 insertions (ex20ins) are targeted by novel compounds in non-small-cell lung cancer (NSCLC). However, data about outcome under conventional therapies and the influence of molecular features are scarce. PATIENTS AND METHODS: We retrospectively analysed 118 patients with evaluation of radiologic response based on RECIST v1.1. TP53 status was available for 88 cases. RESULTS: Platinum doublets and chemoimmunotherapy showed similar response rates (20-25%), disease control rates (80%) and median progression-free survival (mPFS, ≈7 months), which were longer compared to monochemotherapy (9%, 59%, 4.1 months), EGFR inhibitors (0%, 46%, 3.0) and PD-(L)1 inhibitors (0%, 30%, 2.1; p < 0.05). Overall survival (OS) was not dependent on the choice of first-line treatment, but related to more lines of systemic therapy (p < 0.05). TP53 mutations and brain metastases were associated with shorter PFS under platinum doublets and EGFR inhibitors (HR 3.3-6.1, p < 0.01), and shorter OS for patients receiving both treatments (p < 0.05). More tumour CD8+ and less Th1 cells were associated with longer OS independent of brain and TP53 status (p < 0.01). No difference in outcome was noted according to the ex20ins site and use of pemetrexed (vs. other cytotoxics) or bevacizumab. Long-lasting responses (>1 year) occasionally occurred under EGFR inhibitors for both 'near-' and 'far-loop' variants. CONCLUSIONS: Platinum doublets and chemoimmunotherapy have the highest activity with ORR of 20-25% and mPFS of approximately 7 months, regardless of the cytotoxic partner, while PD-(L)1 inhibitors show limited efficacy. TP53 mutations, brain metastases and a lower tumour CD8/Th1-cell ratio are independently associated with shorter survival.

A gene expression signature associated with B cells predicts benefit from immune checkpoint blockade in lung adenocarcinoma.

Immune checkpoint blockade (ICB) expands the therapeutic options for metastatic lung cancer nowadays representing a standard frontline strategy as monotherapy or combination therapy, as well as an option in oncogene-addicted NSCLC after exhaustion of targeted therapies. Predictive markers are urgently needed, since only a minority of patients benefits from ICB, while serious adverse effects of immunotoxicity may occur. The study cohort included 43 ICB-treated metastatic lung adenocarcinoma showing long-term response (n = 16), rapid progression (n = 21) or intermediate patterns of response (n = 6). Lung biopsies acquired before initiation of ICB were analyzed by targeted mRNA expression profiling of 770 genes. Level and proportions of 14 immune cell types were estimated using characteristic gene expression signatures. Abundance of B cells (HR = 0.66, p = .00074), CD45+ cells (HR = 0.61, p = .01) and total TILs (HR = 0.62, p = .025) was associated with prolonged progression-free survival after ICB treatment. In a ROC analysis, B cells (AUC = 0.77, p = .0055) and CD45+ cells (AUC = 0.73, p = .019) predicted benefit of ICB, which was not the case for PD-L1 mRNA (AUC = 0.54, p = .72) and PD-L1 protein expression (AUC = 0.68, p = .082). Clustering of 79 candidate predictive markers identified among 770 investigated genes revealed two distinct predictive clusters which included cytotoxic cell or macrophage markers, respectively. In summary, targeted gene expression profiling was feasible using routine diagnostics biopsies. This study proposes B cells and total TILs as complementary predictors of ICB benefit in NSCLC. While further preferably prospective validation is required, gene expression profiling could be integrated in the routine diagnostic work-up complementing existing NGS protocols.

Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the efficacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMB-high tumor subgroup. Unmet needs include prospective validation of TMB cutoffs in relationship to tumor type and patient outcomes. Furthermore, standardization and harmonization of TMB measurement across test platforms are important to the successful implementation of TMB in clinical practice. SIGNIFICANCE: Evaluation of TMB as a predictive biomarker creates the need to harmonize panel-based TMB estimation and standardize its reporting. TMB can improve the predictive accuracy for immunotherapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors.