Tumor mutational burden assessed by targeted NGS predicts clinical benefit from immune checkpoint inhibitors in non-small cell lung cancer

Efficacy of Pembrolizumab vs. Nivolumab Plus Ipilimumab in Metastatic NSCLC in Relation to PD-L1 and TMB Status

The efficacy of immune checkpoint inhibitor (ICI) therapy concerning programmed death ligand 1 (PD-L1) status is well established in patients diagnosed with non-small cell lung cancer (NSCLC). However, there remains a paucity of evidence regarding the efficacy concerning tumor mutational burden (TMB) in both clinical trials and real-world data (RWD). In the current article, clinicopathological and molecular epidemiological data were meticulously collected, and treatment modalities were meticulously recorded. The final analysis included a study population of 194 patients. Median age was 67 years (range 37-86), with the majority being male (71.13%), and 85.71% of patients were either current or former smokers at diagnosis. Adenocarcinoma accounted for most diagnoses (71.65%), followed by squamous cell carcinoma (24.23%). In terms of PD-L1 status, 42.78% had an expression level below 1%, 28.35% had an expression between 1-49%, and 28.87% had an expression above 50%. The TMB ranged from 0 to 75, with a median of 10.31 (range 0-75) for PD-L1 expression below 1%, with a median of 9.73 (range 0.95-39.63) for PD-L1 expression between 1-49%, and a median of 9.72 (range 0.95-48) for PD-L1 expression above 50%. Corresponding to patients with low PDL-1 less than 1% and low TMB (0-5), the median overall survival (mOS) was 16 (p = 0.18), and 15 months (p = 0.22), patients with medium PDL-1 (1-49%) and medium TMB (5-10), the mOS was 15 (p = 0.18) and 16 months (p = 0.22), patients with high PDL-1 (>50) and high TMB (>10), the mOS was 24 (p = 0.18) and 21 (p = 0.22) months. This study represents the largest academic RWD dataset concerning PD-L1 and TMB status in patients with locally advanced and metastatic NSCLC.

Association between immune-related adverse events and prognosis in patients with advanced non-small cell lung cancer: a systematic review and meta-analysis

Background

The emergence of immune checkpoint inhibitors (ICIs) provides a variety of options for patients with advanced non-small-cell lung cancer (NSCLC). After the application of ICIs, the immune system of patients was highly activated, and immune-related adverse events (irAEs) could occur in some organ systems, and irAEs seemed to be associated with the survival prognosis of patients. Therefore, we evaluated the association between survival outcomes and irAEs in NSCLC patients and conducted a systematic review and meta-analysis.

Methods

We conducted systematic reviews of PubMed, Embase, Cochrane, and Web of Science databases until December 2021. The forest map was constructed by combining the hazard ratio (HR) and 95% confidence interval (CI). I2 estimated the heterogeneity between studies. A meta-analysis was performed using R 4.2.1 software.

Results

Eighteen studies included 4808 patients with advanced NSCLC. In pooled analysis, the occurrence of irAEs was found to be a favorable factor for improved prognosis (PFS: HR: 0.48, 95% CI: 0.41-0.55, P <0.01; OS: HR: 0.46, 95% CI: 0.42-0.52, P <0.01). In subgroup analyses, cutaneous irAE, gastrointestinal irAE, endocrine irAE and grade ≥3 irAEs were associated with improvements in PFS and OS, but pulmonary and hepatic irAEs were not.

Conclusion

Existing evidence suggests that the occurrence of irAEs may be a prognostic biomarker for advanced NSCLC. However, further research is needed to explore the prospect of irAEs as a prognostic biomarker in patients undergoing immunotherapy.

Systematic review registration

https://www.crd.york.ac.uk/PROSPEROFILES/405333_STRATEGY_20240502.pdf, identifier CRD42023405333.

Unraveling the Complexities of Immune Checkpoint Inhibitors in Hepatocellular Carcinoma

Immune checkpoint inhibitors (ICIs) have emerged as effective therapeutics for multiple cancers. Nevertheless, as immunotherapeutic approaches are being extensively utilized, substantial hurdles have arisen for clinicians. These include countering ICIs resistance and ensuring precise efficacy assessments of these drugs, especially in the context of hepatocellular carcinoma (HCC). This review attempts to offer a holistic overview of the latest insights into the ICIs resistance mechanisms in HCC, the molecular underpinnings, and immune response. The intent is to inspire the development of efficacious combination strategies. This review also examines the unconventional response patterns, namely pseudoprogression (PsP) and hyperprogression (HPD). The prompt and rigorous evaluation of these treatment efficacies has emerged as a crucial imperative. Multiple clinical, radiological, and biomarker tests have been advanced to meticulously assess tumor response. Despite progress, precise mechanisms of action and predictive biomarkers remain elusive. This necessitates further investigation through prospective cohort studies in the impending future.

Predictive Biomarkers for Immunotherapy in Gastric Cancer: Current Status and Emerging Prospects

Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.

Predictive value of tumor mutational burden for PD-1/PD-L1 inhibitors in NSCLC: A meta-analysis

BACKGROUND

To investigate the association between tumor mutational burden (TMB) and the therapeutic effect of Programmed Death 1/Programmed Death Ligand 1 inhibitors in non-small cell lung cancer.

METHODS

Four electronic databases, PubMed, Embase, Web of Science, and Cochrane Library, were searched on May 10, 2023, and no time limitation was applied. Analyses were performed using STATA17.0. We assessed the methodological quality of each randomized controlled trial using the Newcastle-Ottawa scale.

RESULTS

After exhaustive database search and rigorous screening, 10 studies were included in the meta-analysis. Our findings indicate that high TMB significantly improves progression-free survival but reduces overall response rate. The overall survival was not significantly different between the high and low TMB groups. No significant publication bias was observed.

CONCLUSION

High TMB serves as a potential predictive biomarker for improved progression-free survival and reduced overall response rate in patients with non-small cell lung cancer treated with programmed death 1/programmed death ligand 1 inhibitors. However, its predictive value in overall survival requires further investigation.

Computational textural mapping harmonises sampling variation and reveals multidimensional histopathological fingerprints

BACKGROUND

Technical factors can bias H&E digital slides potentially compromising computational histopathology studies. Here, we hypothesised that sample quality and sampling variation can introduce even greater and undocumented technical fallacy.

METHODS

Using The Cancer Genome Atlas (TCGA) clear-cell renal cell carcinoma (ccRCC) as a model disease, we annotated ~78,000 image tiles and trained deep learning models to detect histological textures and lymphocyte infiltration at the tumour core and its surrounding margin and correlated these with clinical, immunological, genomic, and transcriptomic profiles.

RESULTS

The models reached 95% validation accuracy for classifying textures and 95% for lymphocyte infiltration enabling reliable profiling of ccRCC samples. We validated the lymphocyte-per-texture distributions in the Helsinki dataset (n = 64). Texture analysis indicated constitutive sampling bias by TCGA clinical centres and technically suboptimal samples. We demonstrate how computational texture mapping (CTM) can abrogate these issues by normalising textural variance. CTM-harmonised histopathological architecture resonated with both expected associations and novel molecular fingerprints. For instance, tumour fibrosis associated with histological grade, epithelial-to-mesenchymal transition, low mutation burden and metastasis.

CONCLUSIONS

This study highlights texture-based standardisation to resolve technical bias in computational histopathology and understand the molecular basis of tissue architecture. All code, data and models are released as a community resource.

Association between baseline C‑reactive protein level and survival outcomes for cancer patients treated with immunotherapy: A meta‑analysis

The prognostic impact of baseline C-reactive protein (CRP) in patients with cancer receiving immune checkpoint inhibitors (ICIs) is unclear. The present meta-analysis aimed to review the prognostic value of baseline C-reactive protein (CRP) levels for patients with cancer receiving immunotherapy. Electronic databases, including PubMed, EMbase, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure, WanFang, Chinese Literature Biomedical Database and Weipu Database, were used to identify cohort studies on the relationship between the baseline CRP levels and ICI survival outcomes from inception to November 2020. Literature screening, data extraction and quality evaluation of studies were independently performed by two reviewers. Subsequently, a meta-analysis was performed using STATA 14.0. A total of 13 cohort studies comprising 2,387 patients with cancer were included in the present meta-analysis. The results indicated that high baseline CRP levels (serum CRP measured within 2 weeks before ICI treatment) were associated with low overall survival (OS) and progression-free survival (PFS) rate among patients treated with ICIs. The subgroup analysis based on cancer type showed that high baseline CRP levels were associated with poor survival outcomes of multiple types of cancer, such as non-small cell lung cancer (6/13; 46.2%), melanoma (2/13; 15.4%), renal cell (3/13; 23.0%) and urothelial carcinoma (2/13; 15.4%). Similar results were observed in subgroup analysis based on the CRP cut-off value of 10 mg/l. In addition, a higher mortality risk was reported in patients with cancer and CRP ≥10 mg/l (hazard ratio, 2.76; 95% CI, 1.70-4.48; P<0.001). Compared with patients with low baseline CRP levels, increased baseline CRP levels were associated with low OS and PFS rate in patients with cancer receiving ICIs. Furthermore, CRP ≥10 mg/l indicated a worse prognosis. Therefore, baseline CRP levels may serve as a marker for the prognosis of patients with certain types of solid tumor treated with ICIs. Due to the limited quality and quantity of included studies, more prospective well-designed studies are required to verify the present findings.

Comparing Genomic Landscapes of Oral and Cutaneous Squamous Cell Carcinoma of the Head and Neck: Quest for Novel Diagnostic Markers

Squamous cell carcinoma is the most common head and neck malignancy arising from the oral mucosa and the skin. The histologic and immunohistochemical features of oral squamous cell carcinoma (OSCC) and head and neck cutaneous squamous cell carcinoma (HNcSCC) are similar, making it difficult to identify the primary site in cases of metastases. With the advent of immunotherapy, reliable distinction of OSCC and HNcSCC at metastatic sites has important treatment and prognostic implications. Here, we investigate and compare the genomic landscape of OSCC and HNcSCC to identify diagnostically useful biomarkers. Whole-genome sequencing data from 57 OSCC and 41 HNcSCC patients were obtained for tumor and matched normal samples. Tumor mutation burden (TMB), Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures, frequent chromosomal alterations, somatic single nucleotide, and copy number variations were analyzed. The median TMB of 3.75 in primary OSCC was significantly lower (P < .001) than that of 147.51 mutations/Mb in primary HNcSCC. The COSMIC mutation signatures were significantly different (P < .001) between OSCC and HNcSCC. OSCC showed COSMIC single-base substitution (SBS) mutation signature 1 and AID/APOBEC activity-associated signature 2 and/or 13. All except 1 HNcSCC from hair-bearing scalp showed UV damage-associated COSMIC SBS mutation signature 7. Both OSCC and HNcSCC demonstrated a predominance of tumor suppressor gene mutations, predominantly TP53. The most frequently mutated oncogenes were PIK3CA and MUC4 in OSCC and HNcSCC, respectively. The metastases of OSCC and HNcSCC demonstrated TMB and COSMIC SBS mutation signatures similar to their primary counterparts. The combination of high TMB and UV signature in a metastatic keratinizing squamous cell carcinoma suggests HNcSCC as the primary site and may also facilitate decisions regarding immunotherapy. HNcSCC and OSCC show distinct genomic profiles despite histologic and immunohistochemical similarities. Their genomic characteristics may underlie differences in behavior and guide treatment decisions in recurrent and metastatic settings.

Combined ARHGEF6 and Tumor Mutational Burden may serve as a potential biomarker for immunotherapy of lung adenocarcinoma

ARHGEF6, a member of the Dbl-related guanylate exchanger (GEF) family, is highly expressed in gastric cancer and glioma. However, scientists still do not know whether it plays a pivotal role in the pathogenesis of lung adenocarcinoma（LUAD）. The prognostic significance of ARHGEF6 expression was assessed by TCGA data. This paper focuses on the level of immune infiltration associated with ARHGEF6 and explored the relationship of this gene with the tumor mutational burden (TMB), immune checkpoints, and drug sensitivity. The results showed that the high expression of ARHGEF6 was associated with a good prognosis in LUAD patients, and positively correlated with a variety of immune cells and drugs. Meanwhile, ARHGEF6 was found to be negatively correlated with TMB. In conclusion, the results of this study suggest that ARHGEF6 is a protective gene in LUAD patients. A combination of ARHGEF6 and TMB could be used as a potential biomarker in the screening of immunotherapy regimens, which are provided to patients with LUAD.

A Machine Learning Approach Using FDG PET-Based Radiomics for Prediction of Tumor Mutational Burden and Prognosis in Stage IV Colorectal Cancer

INTRODUCTION

We assessed the performance of F-18 fluorodeoxyglucose positron emission tomography (FDG PET)-based radiomics for the prediction of tumor mutational burden (TMB) and prognosis using a machine learning (ML) approach in patients with stage IV colorectal cancer (CRC).

METHODS

Ninety-one CRC patients who underwent pretreatment FDG PET/computed tomography (CT) and palliative chemotherapy were retrospectively included. PET-based radiomics were extracted from the primary tumor on PET imaging using the software LIFEx. For feature selection, PET-based radiomics associated with TMB were selected by logistic regression analysis. The performances of seven ML algorithms to predict high TMB were compared by the area under the receiver's operating characteristic curves (AUCs) and validated by five-fold cross-validation. A PET radiomic score was calculated by averaging the z-score of each radiomic feature. The prognostic power of the PET radiomic score was assessed using Cox proportional hazards regression analysis.

RESULTS

Ten significant radiomic features associated with TMB were selected: surface-to-volume ratio, total lesion glycolysis, tumor volume, area, compacity, complexity, entropy, correlation, coarseness, and zone size non-uniformity. The k-nearest neighbors model obtained the good performance for prediction of high TMB (AUC: 0.791, accuracy: 0.814, sensitivity: 0.619, specificity: 0.871). On multivariable Cox regression analysis, the PET radiomic score (Hazard ratio = 4.498, 95% confidential interval = 1.024-19.759; p = 0.046) was a significant independent prognostic factor for OS.

CONCLUSIONS

This study demonstrates that PET-based radiomics are useful image biomarkers for the prediction of TMB status in stage IV CRC. PET radiomic score, which integrates significant radiomic features, has the potential to predict survival in stage IV CRC patients.

Predictive biomarkers and new developments of immunotherapy in gastric cancer: a 2023 update

Gastric cancer is an extremely common digestive tract tumor. The promotion and application of standardized therapy, treatment scheme optimization, and development of new targeted drugs and immunotherapies have improved gastric cancer survival somewhat. However, gastric cancer prognosis generally remains non-optimistic. Immune checkpoint inhibitors (ICI) have gradually become a new choice for gastric cancer treatment and can prolong the survival of some patients. Among them, high-microsatellite instability, Epstein-Barr virus-positive status, or high-tumor mutational burden patients with gastric cancer may be the potential population to benefit from immunotherapy. Nevertheless, there remains a lack of unified and effective predictive markers. Accordingly, this review mainly focused on the possible predictive biomarkers of anti-PD-1/PD-L1 in gastric cancer treatment. Furthermore, the application of anti-PD-1/PD-L1 therapy-related clinical trials on gastric cancer is discussed. The current findings suggest that immunotherapy is a promising application in gastric cancer treatment. Therefore, combining immunotherapy and other therapies may be the trend in the future. Nevertheless, exploring biomarkers to predict ICI response remains a major challenge.

A radiomics nomogram prediction for survival of patients with "driver gene-negative" lung adenocarcinomas (LUAD)

BACKGROUND

To study the role of computed tomography (CT)-derived radiomics features and clinical characteristics on the prognosis of "driver gene-negative" lung adenocarcinoma (LUAD) and to explore the potential molecular biological which may be helpful for patients' individual postoperative care.

METHODS

A total of 180 patients with stage I-III "driver gene-negative" LUAD in the First Affiliated Hospital of Sun Yat-Sen University from September 2003 to June 2015 were retrospectively collected. The Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model was used to screen radiomics features and calculated the Rad-score. The prediction performance of the nomogram model based on radiomics features and clinical characteristics was validated and then assessed with respect to calibration. Gene set enrichment analysis (GSEA) was used to explore the relevant biological pathways.

RESULTS

The radiomics and the clinicopathological characteristics were combined to construct a nomogram resulted in better performance for the estimation of OS (C-index: 0.815; 95% confidence interval [CI]: 0.756-0.874) than the clinicopathological nomogram (C-index: 0.765; 95% CI: 0.692-0.837). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinicopathological nomogram. The clinical prognostic risk score of each patient was calculated based on the radiomics nomogram and divided by X-tile into high-risk (> 65.28) and low-risk (≤ 65.28) groups. GSEA results showed that the low-risk score group was directly related to amino acid metabolism, and the high-risk score group was related to immune and metabolism pathways.

CONCLUSIONS

The radiomics nomogram was promising to predict the prognosis of patients with "driver gene-negative" LUAD. The metabolism and immune-related pathways may provide new treatment orientation for this genetically unique subset of patients, which may serve as a potential tool to guide individual postoperative care for those patients.

Intrinsic features of the cancer cell as drivers of immune checkpoint blockade response and refractoriness

Immune checkpoint blockade represents the latest revolution in cancer treatment by substantially increasing patients' lifetime and quality of life in multiple neoplastic pathologies. However, this new avenue of cancer management appeared extremely beneficial in a minority of cancer types and the sub-population of patients that would benefit from such therapies remain difficult to predict. In this review of the literature, we have summarized important knowledge linking cancer cell characteristics with the response to immunotherapy. Mostly focused on lung cancer, our objective was to illustrate how cancer cell diversity inside a well-defined pathology might explain sensitivity and refractoriness to immunotherapies. We first discuss how genomic instability, epigenetics and innate immune signaling could explain differences in the response to immune checkpoint blockers. Then, in a second part we detailed important notions suggesting that altered cancer cell metabolism, specific oncogenic signaling, tumor suppressor loss as well as tight control of the cGAS/STING pathway in the cancer cells can be associated with resistance to immune checkpoint blockade. At the end, we discussed recent evidences that could suggest that immune checkpoint blockade as first line therapy might shape the cancer cell clones diversity and give rise to the appearance of novel resistance mechanisms.

Predicting response to immune checkpoint blockade in NSCLC with tumour-only RNA-seq

BACKGROUND

Targeted RNA sequencing (RNA-seq) from FFPE specimens is used clinically in cancer for its ability to estimate gene expression and to detect fusions. Using a cohort of NSCLC patients, we sought to determine whether targeted RNA-seq could be used to measure tumour mutational burden (TMB) and the expression of immune-cell-restricted genes from FFPE specimens and whether these could predict response to immune checkpoint blockade.

METHODS

Using The Cancer Genome Atlas LUAD dataset, we developed a method for determining TMB from tumour-only RNA-seq and showed a correlation with DNA sequencing derived TMB calculated from tumour/normal sample pairs (Spearman correlation = 0.79, 95% CI [0.73, 0.83]. We applied this method to targeted sequencing data from our patient cohort and validated these results against TMB estimates obtained using an orthogonal assay (Spearman correlation = 0.49, 95% CI [0.24, 0.68]).

RESULTS

We observed that the RNA measure of TMB was significantly higher in responders to immune blockade treatment (P = 0.028) and that it was predictive of response (AUC = 0.640 with 95% CI [0.493, 0.786]). By contrast, the expression of immune-cell-restricted genes was uncorrelated with patient outcome.

CONCLUSION

TMB calculated from targeted RNA sequencing has a similar diagnostic ability to TMB generated from targeted DNA sequencing.

Biomarkers of response to immunotherapy in early stage non-small cell lung cancer

Immunotherapy with immune-checkpoint inhibitors (ICIs) targeting programmed cell death 1 or programmed death-ligand 1 has revolutionised the treatment of advanced non-small cell lung cancer (NSCLC) and has been investigated in early NSCLC, alone or in combination with chemotherapy, anti-CTLA-4 antibodies and radiotherapy. Although more mature data are needed before setting a change of paradigm in early stages, reports of pathological response rates and disease-free survival are promising, especially with neoadjuvant multimodality approaches. Nevertheless, major pathological response rates for neoadjuvant anti-PD-(L)1 monotherapy rarely exceed 40%, and biomarkers for characterising patients who may benefit the most from ICIs are lacking. These biomarkers have a distinct value from the metastatic setting, with highly different tumour biologies. Among the most investigated so far in this context, programmed death-ligand 1 expression and, to a lesser extent, tumour mutational burden seem to correlate better with higher pathological response rates and survival. Epidermal growth factor receptor, Serine/Threonine Kinase 11and Kelch-like ECH-associated protein 1 mutations rise as essential determinations for the treatment selection in early-stage NSCLC. Emerging and promising approaches comprise evaluation of blood-based ratios, microbiota, and baseline intratumoural TCR clonality. Circulating tumour DNA will be of great help in the near future when selecting best candidates for adjuvant ICIs, monitoring the tumour response to the neoadjuvant treatment in order to improve the rates of complete resections in the early stage.

Elevated PTTG1 predicts poor prognosis in kidney renal clear cell carcinoma and correlates with immunity

Background

PTTG1 has been reported to be linked with the prognosis and progression of various cancers, including kidney renal clear cell carcinoma (KIRC). In this article, we mainly investigated the associations between prognosis, immunity, and PTTG1 in KIRC patients.

Method

We downloaded transcriptome data from the TCGA-KIRC database. PCR and immunohistochemistry were used, respectively, to validate the expression of PTTG1 in KIRC at the cell line and the protein levels. Survival analyses as well as univariate or multivariate Cox hazard regression analyses were used to prove whether PTTG1 alone could affect the prognosis of KIRC. The most important point was to study the relationship between PTTG1 and immunity.

Results

The results of the paper revealed that the expression levels of PTTG1 were elevated in KIRC compared with para-cancerous normal tissues, validated by PCR and immunohistochemistry at the cell line and the protein levels (P < 0.05). High PTTG1 expression was related to shorter overall survival (OS) in patients with KIRC (P < 0.05). Through univariate or multivariate regression analysis, PTTG1 was confirmed to be an independent prognostic factor for OS of KIRC (P < 0.05), and its related seven pathways were obtained through gene set enrichment analysis (GSEA; P < 0.05). Moreover, tumor mutational burden (TMB) and immunity were found to be significantly connected with PTTG1 in KIRC (P < 0.05). Correlations between PTTG1 and immunotherapy responses implied that the low-PTTG1 group was more sensitive to immunotherapy (P < 0.05).

Conclusions

PTTG1 was closely associated with TMB or immunity, and it had a superior ability to forecast the prognosis of KIRC patients.

Immunotherapy resistance in non-small-cell lung cancer: From mechanism to clinical strategies

The high primary resistance incidence and unavoidable secondary resistance are the major clinical obstacle to lasting long-term benefits in Non-small-cell lung cancer (NSCLC) patients treated with immunotherapy. The mechanisms of immunotherapy resistance in NSCLC are complex, mainly involving tumor cells and tumor microenvironment (TME) infiltrating immune cells, including TAMs, B cells, NK cells, and T cells. The selection of clinical strategies for NSCLC progression after immunotherapy resistance should depend on the progressive mode. The progression pattern of NSCLC patients after immunotherapy resistance can be divided into oligo-progression and systemic/multiple progression, which should be considered for further treatment selection. In the future, it needs to explore how to optimize the combined therapy and explore strategies to reprogram infiltrating immune cells under various genetic backgrounds of tumor cells and timely reshape TME during antitumor treatments.

Plasma tumor mutation burden is associated with clinical benefit in patients with non-small cell lung cancer treated with anti-programmed death-1 monotherapy

Background

The clinical utility of plasma tumor mutational burden (pTMB) requires further validation. Herein, the pTMB and genetic alterations were investigated as predictive biomarkers for anti-PD-1 monotherapy outcome in metastatic non-small cell lung cancer (NSCLC).

Methods

The GuardantOMNI panel (Guardant Health) was used to identify pTMB and genetic alterations. Data from 99 patients with metastatic NSCLC treated with pembrolizumab or nivolumab in first-, second-, or third-line settings between June 2016 and December 2020 were collected. Associations between pTMB and clinical benefit rate (CBR, stable disease ⩾6 months or partial response), progression-free survival (PFS), and overall survival (OS) were assessed.

Results

Median pTMB in 84 patients was 10.8 mutations/megabase (mut/Mb). Histological analyses revealed that 61 and 36% of the patients had adenocarcinomas and squamous NSCLC, respectively. Most patients were treated with nivolumab (74%) and most anti-PD-1 agents were administered as second-line treatment (70%). The median follow-up duration was of 10.9 months (range, 0.2-40.7). Patients with high pTMB (⩾19 mut/Mb) had a higher CBR (69%) compared with low pTMB patients (33%; p = 0.01). ARID1A (p = 0.007) and either ERBB2 or KIT mutations (p = 0.012) were positive and negative determinants, respectively, for clinical benefit. Multivariate analysis further showed that high pTMB was an independent predictive biomarker for both PFS [hazard ratio (HR) = 0.44, 95% confidence interval (CI): 0.22-0.88, p = 0.02] and OS (HR = 0.37, 95% CI: 0.18-0.76, p = 0.007).

Conclusion

High pTMB (⩾19 mut/Mb) is significantly associated with CBR in patients with NSCLC treated with anti-PD-1 agents.

Short-term dynamics of circulating tumor DNA predicting efficacy of sintilimab plus docetaxel in second-line treatment of advanced NSCLC: biomarker analysis from a single-arm, phase 2 trial

OBJECTIVE

Robust biomarker predicting efficacy of immunotherapy is limited. Circulating tumor DNA (ctDNA) sought to effectively monitor therapeutic response as well as disease progression. This study aims to investigate predictive role of ctDNA short-term dynamic change (6 weeks postimmunotherapy) in a single-arm, phase 2 trial of sintilimab plus docetaxel for previously treated advanced non-small cell lung cancer (NSCLC) patients.

METHODS

A total of 33 patients with advanced NSCLC with disease progression during or after any first-line treatment were prospectively enrolled between 2019 and 2020. Patients received sintilimab (200 mg, day 1, every 3 weeks) plus docetaxel (75 mg/m², day 3, every 3 weeks) for 4-6 cycles, followed by maintenance therapy with sintilimab (200 mg, day 1, every 3 weeks) until disease progression or unacceptable toxic effects. Blood samples were prospectively collected at baseline, and after 2 cycles of treatment (6 weeks post-treatment). All samples were subjected to targeted next-generation sequencing with a panel of 448 cancer-related genes. The landscape of high-frequency genomic profile of baseline and 6th week was described. Major molecular characteristics in preselected genes of interest associated with response to second-line chemoimmunotherapy were analyzed. The curative effects and prognosis of patients were evaluated.

RESULTS

Patients with ctDNA clearance at 6th week had decreased tumor volume, while most patients with positive ctDNA at 6th-week experienced an increase in tumor volume. Positive 6th-week ctDNA was associated with significantly shorter progression-free survival (PFS) (91 vs NR days; p<0.0001) and overall survival (47 vs 467 days; p =0.0039). Clearance of clonal mutations and none new clonal formation at 6th week were associated with longer PFS (mPFS 89 vs 266 days, p =0.003). ctDNA clearance at 6th week was an independent risk factor for progression or death (HR=100 (95% CI 4.10 to 2503.00), p=0.005).

CONCLUSION

ctDNA status and ctDNA mutation clearance putatively serve as predictive biomarkers for sintilimab combined with docetaxel chemotherapy in pretreated advanced NSCLC patients.

Prognostic impact of tumour mutational burden in resected stage I and II lung adenocarcinomas from a European Thoracic Oncology Platform Lungscape cohort

BACKGROUND

The primary objective of this study is to evaluate tumor mutational burden (TMB), its associations with selected clinicopathological and molecular characteristics as well as its clinical significance, in a retrospective cohort of surgically resected stage I-II lung adenocarcinomas, subset of the ETOP Lungscape cohort.

METHODS

TMB was evaluated on tumor DNA extracted from resected primary lung adenocarcinomas, based on FoundationOne®CDx (F1CDx) genomic profiling, centrally performed at the University Hospital Zurich. The F1CDx test sequences the complete exons of 324 cancer-related genes and detects substitutions, insertions and deletions (indels), copy number alterations and gene rearrangements. In addition, the genomic biomarkers TMB and microsatellite instability (MSI) are analyzed.

RESULTS

In the Lungscape cohort, TMB was assessed in 78 surgically resected lung adenocarcinomas from two Swiss centers (62 % males, 55 %/45 % stage I/II). Median TMB was 7.6 Muts/Mb, with TMB high (≥10 Muts/Mb) in 40 % of cases (95 %CI:29 %-52 %). The most frequently mutated genes were TP53/KRAS/EGFR/MLL2 detected in 58 %/38 %/33 %/30 % of samples, respectively. TMB was significantly higher among males (TMB high: 50 % vs 23 % in females, p = 0.032), as well as among current/former smokers (TMB high: 44 % vs 8 % in never smokers, p = 0.023). Furthermore, TMB was significantly higher in TP53 mutated than in non-mutated patients (TMB high: 60 % vs 12 %, p < 0.001), while it was higher in EGFR non-mutated patients compared to EGFR mutated (TMB high: 48 % vs 23 %, p = 0.049). At a median follow-up time of 56.1 months (IQR:38.8-72.0), none of the three outcome variables (OS, RFS, TTR) differed significantly by TMB status (all p-values > 5 %). This was also true when adjusting for clinicopathological characteristics.

CONCLUSIONS

While presence of TP53 mutations and absence of EGFR mutations are associated with high TMB, increased TMB had no significant prognostic impact in patients with resected stage I/II lung adenocarcinoma beyond T and N classification, in both unadjusted and adjusted analyses.

Definition of a new blood cell count score for early survival prediction for non-small cell lung cancer patients treated with atezolizumab: Integrated analysis of four multicenter clinical trials

Importance

Blood cell count test (BCT) is a robust method that provides direct quantification of various types of immune cells to reveal the immune landscape to predict atezolizumab treatment outcomes for clinicians to decide the next phase of treatment.

Objective

This study aims to define a new BCTscore model to predict atezolizumab treatment benefits in non-small lung cell cancer (NSCLC) patients.

Design, Setting, and Participants

This study analyzed four international, multicenter clinical trials (OAK, BIRCH, POPLAR, and FIR trials) to conduct post-hoc analyses of NSCLC patients undergoing atezolizumab (anti–PD-L1) single-agent treatment (n = 1,479) or docetaxel single-agent treatment (n = 707). BCT was conducted at three time points: pre-treatment (T1), the first day of treatment cycle 3 (T2), and first day of treatment cycle 5 (T3). Univariate and multivariate Cox regression analyses were conducted to identify early BCT biomarkers to predict atezolizumab treatment outcomes in NSCLC patients.

Main Outcomes and Measures

Overall survival (OS) was used as the primary end point, whereas progression-free survival (PFS) according to Response Evaluation Criteria in Solid Tumors (RECIST), clinical benefit (CB), and objective response rate (ORR) were used as secondary end points.

Results

The BCT biomarkers of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at time point T3 and neutrophil-to-monocyte ratio (NMR) at time point T2 with absolute cutoff values of NLR_T3 = 5, PLR_T3 = 180, and NMR_T2 = 6 were identified as strong predictive biomarkers for atezolizumab (Ate)–treated NSCLC patients in comparison with docetaxel (Dtx)–treated patients regarding OS (BCTscore low risk: HR _Ate vs_{. Dtx} = 1.54 (95% CI: 1.04–2.27), P = 0.031; high risk: HR _Ate vs_{. Dtx} = 0.84 (95% CI: 0.62–1.12), P = 0.235). The identified BCTscore model showed better OS AUC in the OAK (AUC_12month = 0.696), BIRCH (AUC_12month = 0.672) and POPLAR+FIR studies (AUC_12month = 0.727) than that of each of the three single BCT biomarkers.

Conclusion and Relevance

The BCTscore model is a valid predictive and prognostic biomarker for early survival prediction in atezolizumab-treated NSCLC patients.

Prognostic Impact of TP53 Mutations and Tumor Mutational Load in Colorectal Cancer

The DNA damage response (DDR) is critical for maintaining genome stability, and abnormal DDR—resulting from mutations in DNA damage-sensing and repair proteins—is a hallmark of cancer. Here, we aimed to investigate the predictive power of DDR gene mutations and the tumor mutational load (TML) for survival outcomes in a cohort of 22 rectal cancer patients who received pre-operative neoadjuvant therapy. Univariate analysis revealed that TML-high and TP53 mutations were significantly associated with worse overall survival (OS) with TML-high retaining significance in multivariate analyses. Kaplan–Meier survival analyses further showed TML-high was associated with worse disease-free (p = 0.036) and OS (p = 0.024) results in our patient cohort. A total of 53 somatic mutations were identified in 22 samples with eight (36%) containing mutations in DDR genes, including ATM, ATR, CHEK2, MRE11A, RAD50, NBN, ERCC2 and TP53. TP53 was the most frequently mutated gene, and TP53 mutations were significantly associated with worse OS (p = 0.023) in Kaplan–Meier survival analyses. Thus, our data indicate that TML and TP53 mutations have prognostic value for rectal cancer patients and may be important independent biomarkers for patient management. This suggests that prognostic determination for rectal cancer patients receiving pre-operative neoadjuvant therapy should include consideration of the initial TML and tumor genetic status.

Significance of a Tumor Mutation Burden Gene Signature with Prognosis and Immune Feature of Gastric Cancer Patients

Gastric cancer (GC) is a common digestive tumor which ranks the fourth most common malignancy worldwide. Immunotherapy is a promising treatment for GC, especially for advanced gastric cancer (AGC). However, in clinical practice, not all patients are sensitive to immunotherapy. Recent studies showed that tumor mutation burden (TMB) is closely correlated with the response of immunotherapy. The current study identified a TMB-related genes' signature to predict the prognosis and immune feature of GC patients. Firstly, we acquired the TMB data and expression data from The Cancer Genome Atlas (TCGA) and the National Center for Biotechnology Information (NCBI) GEO databases. Then, we extracted TMB-related genes from the expression data of TCGA and two GEO cohorts. By using univariate Cox analysis, we identified that the 429 genes were correlated to GC patients' overall survival. Subsequently, an immune prognostic signature was constructed by using the least absolute shrinkage and selection operator analysis (LASSO) and multivariate Cox regression analysis. The signature could be utilized to predict the prognosis of GC patients. In addition, the signature showed a closed correlation with immune feature of GC patients. In conclusion, our risk signature could offer hints for the prognosis of GC patients and might provide insights to formulate new immunotherapy strategies for GC patients.

Mutations in KMT2C, BCOR and KDM5C Predict Response to Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer

Simple Summary

Efficient biomarkers are urgently needed to predict response to immune checkpoint blockade (ICB) therapy for non-small cell lung cancer (NSCLC), particularly NSCLC with low tumor mutational burden (TMB). Here, we show that mutations of three chromatin remodeling-related genes, including KMT2C, BCOR and KDM5C, are associated with the ICB response in NSCLC, including NSCLC with low TMB level. Furthermore, this association is further improved by a combined use of KMT2C/BCOR/KDM5C mutations with TMB or PD-L1 expression. These data suggest that KMT2C/BCOR/KDM5C mutation status has the potential to serve as a predictive biomarker for ICB therapy in NSCLC.

Abstract

Efficient predictive biomarkers are urgently needed to identify non-small cell lung cancer (NSCLC) patients who could benefit from immune checkpoint blockade (ICB) therapy. Since chromatin remodeling is required for DNA repair process, we asked whether mutations in chromatin remodeling genes could increase tumor mutational burden (TMB) and predict response to ICB therapy in NSCLC. Analysis of seven ICB-treated NSCLC cohorts revealed that mutations of three chromatin remodeling-related genes, including KMT2C, BCOR and KDM5C, were significantly associated with ICB response, and combined mutations of these three genes further enhance this association. NSCLC patients with KMT2C/BCOR/KDM5C mutations had comparable clinical outcomes to TMB-high patients in terms of objective response rate, durable clinical benefit and overall survival. Although KMT2C/BCOR/KDM5C mutations were positively correlated with TMB levels in NSCLC, the association of this mutation with better ICB response was independent of tumor TMB and programmed death-ligand 1 (PD-L1) level, and combination of KMT2C/BCOR/KDM5C mutations with TMB or PD-L1 further improve the prediction of ICB response in NSCLC patients. Cancer Genome Atlas (TCGA) pan-cancer analysis suggested that the association of KMT2C/BCOR/KDM5C mutations with ICB response observed here might not result from DNA repair defects. In conclusion, our data indicate that KMT2C/BCOR/KDM5C mutation has the potential to serve as a predictive biomarker, alone or combined with PD-L1 expression or TMB, for ICB therapy in NSCLC.

Evaluation of the TruSight Oncology 500 Assay for Routine Clinical Testing of Tumor Mutational Burden and Clinical Utility for Predicting Response to Pembrolizumab

Pembrolizumab is approved for treating patients with unresectable or metastatic solid tumors with high tumor mutational burden (TMB), as assessed by the Food and Drug Administration-approved companion diagnostic FoundationOneCDx, after progression on prior treatment. To expand TMB assessment for enriching response to pembrolizumab, TMB measurement from TruSight Oncology 500 (TSO500) was evaluated in archival pan-tumor samples from 294 patients enrolled in eight pembrolizumab monotherapy studies. TSO500 is a panel-based next-generation sequencing assay with broad availability, quick turnaround time, and a standardized bioinformatics pipeline. TSO500 TMB was evaluated for correlation and concordance with two reference methods: FoundationOneCDx and whole-exome sequencing. The TSO500 cut-off for TMB-high was selected based on the receiver-operating characteristic curve analysis against each reference method's cut-off for TMB-high. Clinical utility of the selected TSO500 cut-off (10 mutations/Mb) was assessed by calculating the sensitivity, specificity, positive and negative predictive values, and objective response rate enrichment. There was high correlation and concordance of TSO500 TMB with both reference methods. TSO500 TMB was associated significantly with the best overall response, and the selected cut-off had comparable clinical utility with respective cut-offs for the reference methods in predicting response to pembrolizumab. As a commercial assay with global kit distribution complete with an off-the-shelf software package, TSO500 may provide additional access to immunotherapy for patients with tumors with TMB ≥10 mutations/Mb.

mTOR pathway gene mutations predict response to immune checkpoint inhibitors in multiple cancers

BACKGROUND

mTOR pathway is known to promote cancer malignancy and influence cancer immunity but is unknown for its role in immune checkpoint inhibitors (ICI) therapy.

METHODS

Using Memorial Sloan-Kettering Cancer Center dataset (MSKCC), we extracted mTOR pathway gene mutations for stepwise Cox regression in 1661 cancer patients received ICI. We associated the mutation of the gene signature resulted from the stepwise Cox regression with the 1661 patients' survival. Other 553 ICI-treated patients were collected from 6 cohorts for validation. We also performed this survival association in patients without ICI treatment from MSKCC as discovery (n = 2244) and The Cancer Genome Atlas (TCGA) as validation (n = 763). Pathway enrichment analysis were performed using transcriptome profiles from TCGA and IMvigor210 trial to investigate the potential mechanism.

RESULTS

We identified 8 genes involved in mTOR pathway, including FGFR2, PIK3C3, FGFR4, FGFR1, FGF3, AKT1, mTOR, and RPTOR, resulted from stepwise Cox regression in discovery (n = 1661). In both discovery (n = 1661) and validation (n = 553), the mutation of the 8-gene signature was associated with better survival of the patients treated with ICI, which was independent of tumor mutation burden (TMB) and mainly attributed to the missense mutations. This survival association was not observed in patients without ICI therapy. Intriguingly, the mutation of the 8-gene signature was associated with increased TMB and PD1/PD-L1 expression. Immunologically, pathways involved in anti-tumor immune response were enriched in presence of this mutational signature in mTOR pathway, leading to increased infiltration of immune effector cells (e.g., CD8 + T cells, NK cells, and M1 macrophages), but decreased infiltration of immune inhibitory M2 macrophages.

CONCLUSIONS

These results suggested that mTOR pathway gene mutations were predictive of better survival upon ICI treatment in multiple cancers, likely by its association with enhanced anti-tumor immunity. Larger studies are warranted to validate our findings.

Neoadjuvant Chemo-Immunotherapy for Locally Advanced Non-Small-Cell Lung Cancer: A Review of the Literature

Non-small cell lung cancer accounts for approximately 80–85% of all lung cancers and at present represents the main cause of cancer death among both men and women. To date, surgery represents the cornerstone; nevertheless, around 40% of completely resected patients develop disease recurrence. Therefore, combining neoadjuvant chemo-immunotherapy and surgery might lead to improved survival. Immunotherapy is normally well tolerated, although significant adverse reactions have been reported in certain patients treated with inhibitors of immune checkpoints. In this review, we explore the current literature on the use of neoadjuvant chemo-immunotherapy followed by surgery for treatment of locally advanced non-small-cell lung cancer, with particular attention to the histological aspects, ongoing trials, and the most common surgical approaches. In conclusion, neoadjuvant immunotherapy whether combined or not with chemotherapy reveals a promising survival benefit for patients with advanced non-small-cell lung cancer; nevertheless, more data remain necessary to identify the best candidates for neoadjuvant regimens.

Clinical features and prognosis according to genomic mutations in primary and metastatic lesions of non‐small‐cell lung cancer

Non‐small‐cell lung cancer (NSCLC) is an important cause of cancer‐related death worldwide. The distant metastasis heterogeneity of gene tumor mutations in tumors of NSCLC patients brings critical challenges for treatment. We sequenced the primary tumors and metastatic tissues of 48 NSCLC patients through 363 tumor‐related gene panels to examine gene mutations in primary tumors and metastatic tissues, and screen candidate carcinogenic and metastatic‐related driver mutations. The patient group included 21 patients in the metastatic group and 27 patients in the non‐metastatic group. The patient's median age was 62 years and 54% (26/48) of patients were women. Approximately 75% (36/48) of patients were non‐smokers. The mutation spectrum results showed that epidermal growth factor receptor (EGFR) gene mutation was the most frequent mutation (68.75%), followed by TP53 mutation (45.83%); 19del accounted for the largest proportion of EGFR mutations. Copy number variation (CNV) mutation spectrum results showed that EGFR amplification was more common in the metastatic group than the non‐metastatic group. The mutant‐allele tumor heterogeneity value of the metastatic group was higher than that of the non‐metastatic group (p = 0.013). The progression‐free survival of the metastatic group was significantly shorter than that in the non‐metastatic group (p = 0.041). Single nucleotide variant difference analysis showed that the frequency of TP53 mutations was higher in the metastasis group. The number of subclonal mutations in the primary and metastatic lesions in the metastasis group was significantly different; the number of subclonal sites in metastatic lesions was higher than that in primary lesions. Our results suggested that the gene mutations of NSCLC in primary and metastatic lesions and identified specific mutations related to metastasis of NSCLC. Our research will help to clarify key differences between gene mutations between primary and metastatic NSCLC. These findings will help to provide new theoretical support for the future targeted therapy of metastatic NSCLC.

New evaluation of the tumor immune microenvironment of non-small cell lung cancer and its association with prognosis

BACKGROUND

A better understanding of the tumor immune microenvironment (TIME) will facilitate the development of prognostic biomarkers and more effective therapeutic strategies in patients with lung cancer. However, little has been reported on the comprehensive evaluation of complex interactions among cancer cells, immune cells, and local immunosuppressive elements in the TIME.

METHODS

Whole-exome sequencing and RNA sequencing were carried out on 113 lung cancers. We performed single sample gene set enrichment analysis on TIME-related gene sets to develop a new scoring system (TIME score), consisting of T-score (tumor proliferation), I-score (antitumor immunity) and S-score (immunosuppression). Lung cancers were classified according to a combination of high or low T-score, I-score, and S-scores (eight groups; G1-8). Clinical and genomic features, and immune landscape were investigated among eight groups. The external data sets of 990 lung cancers from The Cancer Genome Atlas and 76 melanomas treated with immune checkpoint inhibitors (ICI) were utilized to evaluate TIME scoring and explore prognostic and predictive accuracy.

RESULTS

The representative histological type including adenocarcinoma and squamous cell carcinoma, and driver mutations such as epidermal growth factor receptor and TP53 mutations were different according to the T-score. The numbers of somatic mutations and predicted neoantigens were higher in T^hi (G5-8) than T^lo (G1-4) tumors. Immune selection pressure against neoantigen expression occurred only in T^hi and was dampened in T^hi/I^lo (G5-6), possibly due to a reduced number of T cells with a high proportion of tumor specific but exhausted cells. T^hi/I^lo/S^hi (G5) displayed the lowest immune responses by additional immune suppressive mechanisms. The T-score, I-score and S-scores were independent prognostic factors, with survival curves well separated into eight groups with G5 displaying the worst overall survival, while the opposite group T^lo/I^hi/S^lo (G4) had the best prognosis. Several oncogenic signaling pathways influenced on T-score and I-scores but not S-score, and PI3K pathway alteration correlated with poor prognosis in accordance with higher T-score and lower I-score. Moreover, the TIME score predicted the efficacy of ICI in patients with melanoma.

CONCLUSION

The TIME score capturing complex interactions among tumor proliferation, antitumor immunity and immunosuppression could be useful for prognostic predictions or selection of treatment strategies in patients with lung cancer.

The Predictive Value of Tumor Mutation Burden on Clinical Efficacy of Immune Checkpoint Inhibitors in Melanoma: A Systematic Review and Meta-Analysis

Background: Tumor mutational burden (TMB) is a genomic biomarker that can predict favorable responses to immune checkpoint inhibitors (ICIs). Although we have better understanding of TMB in cancer immunity and cancer immunotherapy, the relationship between TMB and the clinical efficacy of ICIs remains unknown in the treatment of melanoma patients. Here, we conduct a systematic review and meta-analysis to evaluate the predictive value of TMB on the efficacy of ICIs in patients with melanoma.

Methods: We systematically collected data from PubMed, Embase, Cochrane Library, CNKI, China Biomedical Database (CBM), and Wanfang Database. The end date was set to 26 June 2021. We included retrospective studies or clinical trials of ICIs that reported hazard ratios (HRs) for overall survival and/or progression-free survival according to TMB. Data for 1,493 patients from 15 studies were included. In addition, pooled effect size, heterogeneity analysis, sensitivity analysis, publication bias detection, and subgroup analysis were performed based on the included data.

Results: Patients with high TMB showed significantly improved OS (HR = 0.49, 95% CI: 0.33, 0.73; p = 0.001) and PFS (HR = 0.47, 95% CI: 0.33, 0.68; p < 0.001) compared with patients with low TMB. This association was very good in patients treated with monotherapy, that is, anti-CTLA-4 or anti-PD-(L)-1 inhibitors, but not for the patients treated with a combination of the two drugs. The subgroup analysis results showed that heterogeneity was substantial in the targeted next-generation sequencing (NGS) group. Publication bias was detected, and the results were visualized using the funnel chart. And sensitivity analysis and trim-and-fill method analysis showed that our results were stable and reliable.

Conclusion: High TMB is associated with improved OS and PFS in melanoma patients treated with mono-drug ICIs. TMB determined by NGS should be standardized to eliminate heterogeneity. Therefore, the role of TMB in identifying melanoma patients who may benefit from ICI should be further determined in more randomized controlled trials in the future.

The predictive efficacy of tumor mutation burden in immunotherapy across multiple cancer types: A meta-analysis and bioinformatics analysis

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The FDA has approved pembrolizumab in all cancers with TMB > 10Mut/Mb based on the findings from the phase 2 KEYNOTE-158 study. However, predictive efficacy of TMB is greeted with many skepticisms.

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Cancer patients with high TMB have a better prognosis. Notably, there is no evidence shown whether the good prognosis is caused by the tumor itself or by immunotherapy.

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We compared the meta subgroup analysis by tumor types with non-ICIs from TCGA database and found that immunotherapy can increase, not reduce, cancer patients’ OS with high TMB.

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TMB is a promising therapeutic and prognostic biomarker for immunotherapy, which indicates a better ORR, DCB, OS and PFS.

Purpose

To explore the predictive efficacy of tumor mutation burden (TMB) as a potential biomarker for cancer patients treated with Immune checkpoint inhibitors (ICIs).

Methods

We systematically searched PubMed, Cochrane Library, Embase and Web of Science for clinical studies (published between Jan 1, 2014 and Aug 30, 2021) comparing immunotherapy patients with high TMB to patients with low TMB. Our main endpoints were objective response rate (ORR), durable clinical benefit (DCB), overall survival (OS) and progress-free Survival (PFS). Moreover, we downloaded simple nucleotide variation (SNV) data of 33 major cancer types from the TCGA database as non-ICIs group, and compared the high TMB patients’ OS between the non-ICIs group and meta-analysis results.

Results

Of 10,450 identified studies, 41 were eligible and were included in our analysis (7713 participants). Compared with low TMB patients receiving ICIs, high TMB yielded a better ORR (RR = 2.73; 95% CI: 2.31–3.22; P = 0.043) and DCB (RR = 1.93; 95% CI: 1.64–2.28; P = 0.356), and a significantly increased OS (HR =0.24; 95% CI: 0.21–0.28; P < 0.001) and PFS (HR = 0.38; 95% CI: 0.34–0.42; P < 0.001). Furthermore, compared with non-ICIs group from the TCGA database, immunotherapy can improve OS in some cancer types with high TMB and better prognosis, including colorectal cancer, gastric cancer, lung cancer, melanoma and pan-cancer.

Conclusion

TMB is a promising therapeutic and prognostic biomarker for immunotherapy, which indicates a better ORR, DCB, OS and PFS. If there is a standard for TMB assessment and cut-off, it could improve the management of different cancers.

Predictive value of tumor mutational burden for immunotherapy in non-small cell lung cancer: A systematic review and meta-analysis

Background

Immunotherapy has emerged as a promising treatment for non-small cell lung cancer (NSCLC). Yet, some patients cannot benefit from immunotherapy, and reliable biomarkers for selecting sensitive patients are needed. Herein, we performed a meta-analysis to evaluate the predictive value of tumor mutational burden (TMB) in NSCLC patients treated with immunotherapy.

Methods

Eligible studies were comprehensively searched from electronic databases prior to August 31, 2021. Meta-analyses of high TMB versus low TMB as well as immunotherapy versus chemotherapy in patients with high/low TMB were conducted. Hazard ratio (HR) with corresponding 95% confidence interval (95%CI) for progression-free survival (PFS) and overall survival (OS) and odds ratio (OR) with 95%CI for objective response rate (ORR) were calculated.

Results

A total of 31 datasets (3437 patients) and 6 randomized controlled trials (3662 patients) were available for meta-analyses of high TMB versus low TMB and immunotherapy versus chemotherapy, respectively. High TMB predicted significantly favorable PFS (HR = 0.54, 95%CI: 0.46–0.63, P<0.001) and OS (HR = 0.70, 95%CI: 0.57–0.87, P = 0.001), and higher ORR (OR = 3.14, 95%CI: 2.28–4.34, P<0.001) compared with low TMB. In patients with high TMB, immunotherapy was associated with improved PFS (HR = 0.62, 95%CI: 0.53–0.72), OS (HR = 0.67, 95%CI: 0.57–0.79) and ORR (OR = 2.35, 95%CI: 1.74–3.18) when compared with chemotherapy. However, in patients with low TMB, immunotherapy seemed to predict inferior PFS (HR = 1.20, 95%CI: 1.02–1.41) and ORR (OR = 0.61, 95%CI: 0.44–0.84) and have no OS benefit (HR = 0.88, 95%CI: 0.74–1.05) as compared with chemotherapy.

Conclusion

This meta-analysis demonstrates more clinical benefits concerning treatment response and survival outcomes in high-TMB NSCLC patients who are treated with immunotherapy. TMB is a promising biomarker for discriminating NSCLC patients who can benefit more from immunotherapy.

The key to immunotherapy: how to choose better therapeutic biomarkers for patients with non-small cell lung cancer

Immunotherapy has become the standard of care for non-small cell lung cancer (NSCLC), either in combination or monotherapy. However, there are still some patients who cannot benefit from it. Immunization strategies for NSCLC are based on the expression of PD-L1 on tumor cells and TMB, and although these indicators have a certain predictive effect, their predictive performance is not good. Therefore, clinicians must make adjustments to recognize markers. This is a review article that summarized immunotherapeutic biomarkers according to the "seed-soil-environment", generalizes primary resistance to immunotherapy, and summarizes the integration of markers.

T cell subtype profiling measures exhaustion and predicts anti-PD-1 response

Anti-PD-1 therapy can provide long, durable benefit to a fraction of patients. The on-label PD-L1 test, however, does not accurately predict response. To build a better biomarker, we created a method called T Cell Subtype Profiling (TCSP) that characterizes the abundance of T cell subtypes (TCSs) in FFPE specimens using five RNA models. These TCS RNA models are created using functional methods, and robustly discriminate between naïve, activated, exhausted, effector memory, and central memory TCSs, without the reliance on non-specific, classical markers. TCSP is analytically valid and corroborates associations between TCSs and clinical outcomes. Multianalyte biomarkers based on TCS estimates predicted response to anti-PD-1 therapy in three different cancers and outperformed the indicated PD-L1 test, as well as Tumor Mutational Burden. Given the utility of TCSP, we investigated the abundance of TCSs in TCGA cancers and created a portal to enable researchers to discover other TCSP-based biomarkers.

Integrative Genomic Analyses of 1,145 Patient Samples Reveal New Biomarkers in Esophageal Squamous Cell Carcinoma

Due to the lack of effective diagnostic markers and therapeutic targets, esophageal squamous cell carcinoma (ESCC) shows a poor 5 years survival rate of less than 30%. To explore the potential therapeutic targets of ESCC, we integrated and reanalyzed the mutation data of WGS (whole genome sequencing) or WES (whole exome sequencing) from a total of 1,145 samples in 7 large ESCC cohorts, including 270 ESCC gene expression data. Two new mutation signatures and 20 driver genes were identified in our study. Among them, AP3S1, MUC16, and RPS15 were reported for the first time. We also discovered that the KMT2D was associated with the multiple clinical characteristics of ESCC, and KMT2D knockdown cells showed enhanced cell migration and cell invasion. Furthermore, a few neoantigens were shared between ESCC patients. For ESCC, compared to TMB, neoantigen might be treated as a better immunotherapy biomarker. Our research expands the understanding of ESCC mutations and helps the identification of ESCC biomarkers, especially for immunotherapy biomarkers.

PD-L1 expression and Tumor mutation burden as Pathological response biomarkers of Neoadjuvant immunotherapy for Early-stage Non-small cell lung cancer: A systematic review and meta-analysis

To date, there is no approved biomarker for predicting pathological response in neoadjuvant programmed cell death (ligand) 1 (PD-(L)1) blockades treated early-stage non-small cell lung cancer (NSCLC). Databases including PubMed, Embase, ClinicalTrials.gov, and Conference abstracts were searched for clinical trials of neoadjuvant PD-1/PD-L1 blockades for resectable NSCLC. Data regarding major pathological response (MPR), pathological complete response (pCR) in patients with high/low pretreatment PD-L1 expression, and tumor mutation burden (TMB) were synthesized using fixed-model meta-analysis and evaluated by odds ratio with 95% confidence interval. This analysis included 10 studies involving 461 NSCLC patients. Compared with PD-L1 expression <1%, PD-L1 expression ≥1% is associated with a higher rate of MPR and pCR. High-TMB associated with MPR and pCR. Similar findings were observed in subgroup analyses despite mono-PD-1/PD-L1 blockade or their combination with chemotherapy. Notably, 50% as the cutoff value for PD-L1 expression demonstrated better prediction efficacy for MPR than that of 1%.

Preanalytical Variables and Sample Quality Control for Clinical Variant Analysis

Broad molecular profiling by next-generation sequencing of solid tumors has become a critical tool for clinical decision-making in the era of precision oncology. In addition to many already approved targeted therapies, more than half of ongoing oncology-related clinical trials are biomarker-driven. Therefore, accurate and reliable assays are needed to assess the genetic make-up of tumor cells and guide clinicians in the therapy decision process. In order to obtain high-quality NGS data for variant detection, certain preanalytical steps and quality metrics should be followed. These include assessment of sample types, choice of extraction method, library preparation technology, sequencing platform, and finally sequencing quality control. Each of these steps has certain challenges and pitfalls that need to be addressed and overcome, respectively. In this chapter, we address the preanalytical quality control and how each of the involved steps may influence the final result. Following these guidelines and QC metrics may help in obtaining optimal results that will allow the precise and robust assessment of genetic variants in a clinical setting.

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

BACKGROUND

Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications.

MATERIALS AND METHODS

Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values.

RESULTS

Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples.

CONCLUSIONS

Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Genomic landscape of treatment refractory metastatic colorectal cancer

BACKGROUND

Metastatic colorectal cancer (mCRC) is a complex and heterogeneous disease with few standard and targeted treatment options. Next-generation sequencing of tumor tissue was performed to identify cancer driver mutations to discover possible personalized treatment options, as targeted treatment possibilities are limited for this patient population. Results of genomic sequencing in patients with treatment-refractory mCRC are described in this retrospective analysis.

MATERIAL AND METHODS

Clinico-pathological characteristics and genomic sequence results of consecutive patients with refractory mCRC, referred to the Experimental Cancer Therapy Unit (ECTU) at Department of Oncology, Herlev & Gentofte Hospital in the period from 1 October 2015 to 14 December 2018 were reviewed in this retrospective analysis. Tumor tissue from the patients was analyzed by next-generation sequencing using the Oncomine Comprehensive primer panel to detect actionable variants of cancer driver mutations and microsatellite instability status. From August 2018 tumor mutational burden was also analyzed.

RESULTS

A total of 80 patients with treatment-refractory mCRC and in a fairly good performance were referred to the ECTU during this period. Genomic sequencing of tumor tissue was performed for all 80 patients and a cancer driver mutation was identified in 90% (n = 72) of the patients. A total of 31.3% (n = 25) of the patients received therapy either as targetable therapy outside an available trial (n = 2), FDA approved therapy (n = 2), or treatment in phase 1 or 2 trials, independent of the genomic signature 26.3% (n = 21).

CONCLUSION

Most mCRC patients refractory to standard anti-neoplastic therapies, presented with a cancer driver mutation, however, only a few of these mutations gave rise to matched therapies as only 2.5% of the patients from this period received targeted therapy.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

The Prognostic Value of ctDNA and bTMB on Immune Checkpoint Inhibitors in Human Cancer

Background

Circulating tumor DNA (ctDNA) levels and blood tumor mutation burden (bTMB) have a significant impact on the prognosis of tumor patients. However, their prognostic role in immune checkpoint inhibitors (ICIs) in cancer patients is still unclear.

Methods

We used the Review Manager software (version 5.3) to perform a meta-analysis based on the published literature to explore the prognostic value of ctDNA and bTMB in patients receiving immunotherapy. We extracted the hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS) for each included study and their respective 95% confidence intervals (CIs) and p-values for analysis.

Results

Thirteen studies were included in the meta-analysis. Higher ctDNA levels were significantly associated with shorter OS (HR = 3.35, 95%CI = 2.49–4.51, p < 0.00001) and PFS (HR = 3.28, 95%CI = 2.47–4.35, p < 0.00001). The results of ctDNA subgroup analysis showed that high posttreatment ctDNA levels significantly correlated with shorter OS in cancer patients receiving ICIs (HR = 5.09, 95%CI = 1.43–18.07, p = 0.01). Moreover, patients with ctDNA clearance had better OS (HR = 4.94, 95%CI = 2.96–8.26, p < 0.00001). Patients with high posttreatment ctDNA levels had shorter PFS (HR = 3.00, 95%CI = 2.02–4.46, p < 0.00001) and those with ctDNA clearance had longer PFS (HR = 4.61, 95%CI = 2.78–7.65, p < 0.00001). However, there was no statistically significant difference in the OS benefits between a high and a low bTMB after ICI therapy (HR = 0.68, 95%CI = 0.33–1.37, p = 0.28).

Conclusions

The host immune system and tumor burden together determine whether cancer patients can benefit from ICI therapy. Our systematic review and meta-analysis revealed for the first time that the levels of pretreatment and posttreatment ctDNA and the clearance of ctDNA can independently be used as prognostic factors for antitumor immunotherapy, while bTMB cannot. In conclusion, ctDNA levels have great potential as an assistant tool for radiological assessments to make clinical therapeutic decisions. The prognostic utility of bTMB still requires further exploration.

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).

Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.

Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4⁺ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.

Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

ctDNA-Profiling-Based UBL Biological Process Mutation Status as a Predictor of Atezolizumab Response Among TP53-Negative NSCLC Patients

Atezolizumab, an immune checkpoint inhibitor, has been approved for use in clinical practice in non-small cell lung cancer (NSCLC) patients, but potential biomarkers for response stratification still need further screening. In the present study, a total of 399 patients with high-quality ctDNA profiling results were included. The mutation status of ubiquitin-like conjugation (UBL) biological process genes (including ABL1, APC, LRP6, FUBP1, KEAP1, and TOP2A) and clinical information were further integrated. The results suggested that the patients with the clinical characteristics of male or history of smoking had a higher frequency of UBL mutation positivity [UBL (+)]; the patients who were UBL (+) had shorter progression-free survival (PFS) (1.69 vs. 3.22 months, p = 0.0007) and overall survival (8.61 vs. 16.10 months, p < 0.0001) than those patients with UBL mutation negativity [UBL (–)]; and more promising predictive values were shown in the smoker subgroup and ≤ 3 metastasis subgroup. More interestingly, we found the predictor has more performance in TP53-negative cohorts [training in an independent POPLAR and OAK cohorts (n = 200), and validation in an independent MSKCC cohort (n = 127)]. Overall, this study provides a predictor, UBL biological process gene mutation status, not only for identifying NSCLC patients who may respond to atezolizumab therapy but also for screening out the potential NSCLC responders who received other immune checkpoint inhibitors.

FGFR2 alteration as a potential therapeutic target in poorly cohesive gastric carcinoma

Background

Poorly cohesive (PC) is a unique histologic subtype of gastric cancer (GC), with an increasing incidence in recent years. However, the molecular characteristics and therapeutic targets of PC GC are not yet well studied and there are no effective therapies for these patients.

Methods

Formalin fixed paraffin embedded (FFPE) samples of 556 GC patients, including 64 PC GC, were collected for next-generation sequencing (NGS). Clinical characteristics and genomic profiling were analyzed. FGFR2 expression was detected by quantitative real time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). FGFR2 inhibitors response was studied in vitro.

Results

Among 556 GC patients, PC GC patients were younger (P = 0.004), had lower tumor mutation burden (TMB-L) (P = 0.001) than non-PC GC. The top 10 most frequently mutated genes in PC GC were TP53 (48%), CDH1 (31%), ARID1A (14%), FGFR2 (14%), ERBB2 (9%), CDKN2A (9%), FGF3 (8%), LRP1B (9%), FGF19 (8%) and FGF4 (8%). Noticeably, FGFR2 is more frequently mutated than non-PC GC (14% vs. 6%, P = 0.037), including copy number variants (CNVs, 12.5%) and gene rearrangements (3.1%, FGFR2/VTI1A and FGFR2/TACC2). Former studies have confirmed that gain of copy number could increase FGFR2 expression and sensitivity to FGFR2 inhibitors in GC. However, no research has verified the function of FGFR2 rearrangements in GC. Our results showed that cell lines of GC transfected with TACC2-FGFR2 fusion had increased mRNA and protein expression of FGFR2, and were more sensitive to FGFR2 inhibitors. FGFR2 inhibitors might be a new therapeutic target for PC GC. In addition, we found patients of PC GC harboring gene rearrangements (n = 9) had poorer overall survival (OS) in comparison with patients without any gene rearrangement (n = 19) (16.0 months vs 21.0 months, P = 0.043). Gene rearrangement might be an adverse prognostic factor for PC GC patients.

Conclusions

FGFR2 alterations were recurrent in PC GC and FGFR2 inhibitors might be a new therapeutic target for PC GC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03079-8.

Assessment of TMB, PD-L1, and lymphocyte to monocyte ratio as predictive potential in a phase Ib study of sintilimab in patients with advanced solid tumors

BACKGROUND

Sintilimab is a humanized monoclonal antibody against the programmed cell death 1 (PD-L1). We aimed to assess the safety and activity of sintilimab monotherapy or in combination with chemotherapy in advanced solid tumors.

METHODS

This phase Ib study included six cohorts. Cohort A-C were sintilimab monotherapy settings, and enrolled pretreated patients (2/3 L cohorts). Cohort D-F were treatment-naïve patients (1 L cohorts), and received sintilimab plus different chemotherapies. The primary endpoints were safety and objective response rate (ORR). Exploratory endpoints were potential biomarkers for the prognosis after treatment, such as tumor mutation burden scores (TMB), PD-L1 and lymphocyte-to-monocyte ratio (LMR).

RESULTS

The ORR was 14.6% in the 2/3 L cohorts (n=146), and 73.2% in the 1 L cohorts (n=61). The incidence of grade 3-4 adverse events occurred in 55 patients (37.7%) in 2/3 L cohorts, and in 38 (62.3%) in 1 L cohorts. 157 patients had available TMB scores, and in 2/3 L cohorts, patients in the high TMB groups (TMB≥10) showed a longer progression-free survival (PFS) and overall survival (OS) than those in the low TMB groups (TMB<10). No significant differences in PFS and OS were observed across different PD-L1 groups in both 1 L and 2/3 L cohorts. A high LMR was significantly associated with an improved PFS in 1 L cohorts (P=0.022).

CONCLUSION

Sintilimab alone or combined with chemotherapy had a tolerable safety profile in solid tumors. The combination therapy showed a favorable activity with advanced non-small cell lung cancer and gastric or esophagogastric junction adenocarcinoma. LMR might be a prognostic factor for the combination regimen in these patients.

TRIAL REGISTRATION

ClinicalTrials.gov, number NCT02937116. Registered 18 October 2016.

Assessing tumor heterogeneity: integrating tissue and circulating tumor DNA (ctDNA) analysis in the era of immuno-oncology - blood TMB is not the same as tissue TMB

Tissue tumor mutational burden (tTMB) is calculated to aid in cancer treatment selection. High tTMB predicts a favorable response to immunotherapy in patients with non-small cell lung cancer. Blood TMB (bTMB) from circulating tumor DNA is reported to have similar predictive power and has been proposed as an alternative to tTMB. Across many studies not only are tTMB and bTMB not concordant but also as reported previously by our group predict conflicting outcomes. This implies that bTMB is not a substitute for tTMB, but rather a composite index that may encompass tumor heterogeneity. Here, we provide a thorough overview of the predictive power of TMB, discuss the use of tumor heterogeneity alongside TMB to predict treatment response and review several methods of tumor heterogeneity assessment. Furthermore, we propose a hypothetical method of estimating tumor heterogeneity and touch on its clinical implications.

Real-World Data on NGS Diagnostics: a survey from the Italian Society of Pathology (SIAPeC) NGS Network

Next Generation Sequencing (NGS) is increasingly used in diagnostic centers for the assessment of genomic alterations to select patients for precision oncology. The Italian Society of Anatomic Pathology and Diagnostic Cytopathology (SIAPEC) through the Molecular Pathology and Predictive Medicine Study Group (PMMP) has been following the progressive development of centers that have adopted NGS technology in diagnostics over time. In July 2017, a study network on massive parallel sequencing was activated in Italy and recognized as the NGS SIAPeC National Network by the SIAPeC Scientific Society Board. Since then, activities have been implemented within the network that provide for alignment of laboratories through diagnostic concordance analysis and monitoring of centers adhering to the Network. Recently, considering the growing need for extended genomic analyses, the PMMP distributed a national survey to assess activities related to the use of genomic diagnostics in oncology within the NGS SIAPEC National Network.

Thirty centers participated in the survey. Eighty percent of the centers are laboratories within Pathology Departments. The distribution of laboratories in the country, the diagnostic laboratory/population ratio, the staff dedicated, the type and number of sequencing and mechatronics platforms available, the genomic panels utilized, and the type and number of diagnostic tests carried out in the last year in each center, are reported.

The centers were also asked whether they participated in a multidisciplinary Molecular Tumor Board (MTB) for management of patients. Thirty percent of the centers had a MTB that was ratified by regional decree. The professionals most frequently involved in the core team of the MTB are the pathologist, oncologist, molecular biologist, geneticist, pharmacologist, and bioinformatician.

The data from this survey indicate that NGS diagnostics in Italy is still heterogeneous in terms of geographical distribution and the characteristics of laboratories and diagnostic test performed. The implementation of activities that favors harmonization, the logistics and the convergence of biological material in reference centers for molecular analyses is a priority for the development of a functional laboratory network.

Prognostic effect of coexisting TP53 and ZFHX3 mutations in non-small cell lung cancer patients treated with immune checkpoint inhibitors

In recent years, immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of patients with advanced-stage non-small cell lung cancer (NSCLC). The relationship between TP53 mutation and prognosis of non-small cell lung cancer (NSCLC) remains controversial. We aimed to identify advanced-stage NSCLC patients harboring TP53 mutation who would benefit from ICI treatment. Gene mutations and tumor mutational burden (TMB) data of NSCLC patients who received at least one dose of ICI therapy at the Memorial Sloan Kettering Cancer Center between 2013 and 2017 were extracted from the cBioPortal online platform. Gene clustering analyses were performed for patients with short and long overall survival (OS). The top ten significantly different mutated genes were identified. Furthermore, we analyzed the different OS of coexisting TP53 and other significantly different mutated genes to identify NSCLC patients with TP53 mutations who would benefit from immunotherapy. A total of 350 patients were enrolled in the study. Of these a total of 219 (62.6%) patients were found to harbor TP53 mutations, whereas 131 (37.4%) had wild-type TP53. There was no statistically significant difference in OS between TP53 mutated or wild-type NSCLC patients who underwent ICI treatment. However, coexisting TP53 and ZFHX3 mutations were independent prognostic factors. Higher somatic TMB (highest 20% in each histology) and combination of anti-CTLA-4 and anti-PD-1/PD-L1 therapy were also associated with longer OS in multivariate analysis. Coexisting TP53 and ZFHX3 mutations are independent prognostic factors for advanced-stage NSCLC patients undergoing ICI treatment. These findings could help identify patients harboring TP53 mutations that would benefit from ICI treatment.

Programmed cell death-ligand 1 expression in hepatocellular carcinoma and its correlation with clinicopathological characteristics

BACKGROUND AND AIM

Programmed cell death-ligand 1 (PD-L1) immunohistochemistry score has been approved as the predictive biomarker for anti-PD1/PD-L1 therapy in several advanced malignancies. Although its predictive role remained inconclusive in hepatocellular carcinoma, ongoing study of anti-PD1/PD-L1 therapy showed promising results. However, less is known about the PD-L1 immunohistochemistry score and factors correlated with it in hepatocellular carcinoma. We investigated PD-L1 immunohistochemistry scores in a large cohort of hepatocellular carcinoma, as well as its correlation with various clinical and genomic factors.

METHODS

Immunohistochemistry was performed to detect the expression of PD-L1 protein in 315 hepatocellular carcinoma tissues. All slides were independently reviewed by three senior pathologists. Next-generation YS panel (450 genes) sequencing was performed on 309 patients.

RESULTS

Higher PD-L1 expression as measured by combined positive score (CPS) was associated with increased Edmondson-Steiner grade (grade III vs II, P = 0.041) and TP53 mutations (P = 0.021). PD-L1 CPS had no correlation with tumor mutational burden (Spearman's correlation coefficient 0.067). PD-L1 CPS was not significantly associated with hepatitis B virus infection.

CONCLUSIONS

Our data indicated that patients with higher Edmondson-Steiner grade (grade III) had significantly higher PD-L1 CPS than patients with lower Edmondson-Steiner grade (grade II). Patients with TP53 mutations had significantly higher PD-L1 expression.

Acute anti-Ma2 paraneoplastic encephalitis associated to pembrolizumab: a case report and review of literature

Anti-Ma2 encephalitis is a rare neurological disorder with a predominant involvement of brainstem, limbic and diencephalic structures. Although an unspecific encephalopathy is the usual form of presentation, acute-onset neurologic symptoms and other atypical manifestations have been described and account for the challenging diagnosis of this entity. Despite being usually detected as a paraneoplastic syndrome in patients with early-stage tumors or without a previous history of malignancy, a growing concern has arisen from several cases reported in metastatic patients under treatment with immune checkpoint inhibitors. We report what to our knowledge is the first known case of anti-Ma2 encephalitis associated to pembrolizumab and presenting as an acute-onset focal neurological syndrome, consisting on acute global aphasia, right upper limb paresia, hypoacusia, sleep disorder, decreased conscious level and a motor focal status that was refractory to anticonvulsant therapy. A brain MRI scan showed a focal alteration of the cortical-subcortical signal on the left parietal lobe. CSF study found a significant hyperproteinorrhachia and electroencephalography showed lateralized periodic discharges (LPDs), suggestive of a diffuse encephalopathy. A positive result for anti-Ma2 antibodies was obtained both in blood and CSF samples through indirect immune-fluorescence (IFI) and later confirmed by western-blot technique. Our patient obtained a mild response to steroid therapy and a significant improvement after the administration of intravenous immunoglobulins. The hypothesis that checkpoint inhibitors may trigger the expression of previously subclinical paraneoplastic events, through the strengthening of cytotoxic T cells-mediated immune response, is supported by our finding of preexisting anti-Ma2 antibodies in preserved blood samples obtained before the initiation of pembrolizumab in our patient. Further research is needed to reveal if the detection of onconeural antibodies prior to a treatment with checkpoint inhibitors may be used as a predictive biomarker of neurologic immune-related high-grade toxicity.