Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors

Molecular genetic characteristics of thymic epithelial tumors with distinct histological subtypes

BACKGROUND

Due to the low incidence and histological heterogeneity, the molecular features and underlying carcinogenic mechanisms of thymic epithelial tumors (TETs) are yet to be fully elucidated, especially for different subtypes of TETs.

METHODS

Tumor tissue samples of 43 TETs with distinct histological subtypes were collected. We analyzed the molecular characteristics in different subtypes based on whole exome sequencing data.

RESULTS

The mutational profiles of the different subtypes of TETs varied. Compared with thymomas, thymic carcinomas (TCs) had a higher mutation frequency of MYO16 (33% vs. 3%, p = 0.024) and a lower frequency of ZNF729 mutations (0% vs. 35%, p = 0.044). No significant difference was observed in the median tumor mutation burden across different subtypes. The value of copy number variation burden, weighted genome instability index, and the number of amplified segments were all higher in TCs than thymomas, and they also tended to be higher in B3 thymoma than in non-B3 thymomas, while they had no significant differences between B3 thymoma and TCs. Clustering analyses revealed that Wnt, MAPK, Hedgehog, AMPK, and cell junction assembly signaling pathways were exclusively enriched in non-B3 thymomas, lysine degradation pathway in B3 thymoma, and extracellular matrix-receptor (ECM-receptor) interaction, positive regulation of cell cycle process, and activation of innate immune response pathways in TCs.

CONCLUSIONS

This study revealed distinct molecular landscapes of different subtypes of TETs, suggesting diverse pathogenesis of non-B3 thymomas, B3 thymomas, and TCs. Our findings warrant further validation in future large-scale studies and may provide a theoretical basis for potential personalized therapeutic strategies.

Antigen discovery for the development of cancer immunotherapy

Central to successful cancer immunotherapy is effective T cell antitumor immunity. Multiple targeted immunotherapies engineered to invigorate T cell-driven antitumor immunity rely on identifying the repertoire of T cell antigens expressed on the tumor cell surface. Mass spectrometry-based survey of such antigens ("immunopeptidomics") combined with other omics platforms and computational algorithms has been instrumental in identifying and quantifying tumor-derived T cell antigens. In this review, we discuss the types of tumor antigens that have emerged for targeted cancer immunotherapy and the immunopeptidomics methods that are central in MHC peptide identification and quantification. We provide an overview of the strength and limitations of mass spectrometry-driven approaches and how they have been integrated with other technologies to discover targetable T cell antigens for cancer immunotherapy. We highlight some of the emerging cancer immunotherapies that successfully capitalized on immunopeptidomics, their challenges, and mass spectrometry-based strategies that can support their development.

Impact of tissue-agnostic approvals for patients with gastrointestinal malignancies

Gastrointestinal (GI) malignancies encompass a broad range of tumors with limited treatment options, particularly for advanced disease. With the development and implementation of next-generation sequencing (NGS) in routine practice, molecular-targeting therapies have been increasingly incorporated into the treatment paradigm for various cancers. Several drugs have achieved tissue-agnostic regulatory approvals, which offer promising biomarker-driven therapy options for patients with advanced GI malignancies. In this review, we focus on the clinical evidence for recent drug approvals for neurotrophic tyrosine receptor kinase (NTRK) fusion, microsatellite instability-high (MSI-H) phenotype, tumor mutation burden-high (TMB-H), BRAF V600E, and rearranged during transfection (RET), in the context of GI malignancies. We also highlight the future landscape of tissue-agnostic targets, such as human epidermal growth factor receptor 2 (HER2)/neu, fibroblast growth factor receptor (FGFR), and neuregulin (NRG)-1.

Tissue- and liquid biopsy-based biomarkers for immunotherapy in breast cancer

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and now represent the mainstay of treatment for many tumor types, including triple-negative breast cancer and two agnostic registrations. However, despite impressive durable responses suggestive of an even curative potential in some cases, most patients receiving ICIs do not derive a substantial benefit, highlighting the need for more precise patient selection and stratification. The identification of predictive biomarkers of response to ICIs may play a pivotal role in optimizing the therapeutic use of such compounds. In this Review, we describe the current landscape of tissue and blood biomarkers that could serve as predictive factors for ICI treatment in breast cancer. The integration of these biomarkers in a "holistic" perspective aimed at developing comprehensive panels of multiple predictive factors will be a major step forward towards precision immune-oncology.

A novel cuproptosis-related lncRNA signature to predict prognosis and immune landscape of lung adenocarcinoma

Background

Cuproptosis, a recently discovered type of programmed cell death (PCD), paves a new avenue for cancer treatment. It has been revealed that PCD-related lncRNAs play a critical role in various biological processes of lung adenocarcinoma (LUAD). However, the role of cuproptosis-related lncRNA (CuRLs) remains unclear. This study aimed to identify and validate a CuRLs-based signature for the prognostic prediction of patients with LUAD.

Methods

RNA sequencing data and clinical information of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Pearson correlation analysis was used to identify CuRLs. Univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, and stepwise multivariate Cox analysis were applied to construct a novel prognostic CuRLs signature. A nomogram was developed for the prediction of patient survival outcomes. Gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were utilized to explore potential functions underlying the CuRLs signature. Patients were divided into low- and high-risk groups. Several algorithms, such as tumor immune estimation resource (TIMER), cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and QuanTIseq, were combined to comprehensively investigate the differences in immune landscape between different risk groups. Sensitivity to common anticancer drugs was analyzed using the pRRophetic algorithm.

Results

We constructed a novel prognostic signature based on 10 CuRLs, including CARD8-AS1, RUNDC3A-AS1, TMPO-AS1, MIR31HG, SEPSECS-AS1, DLGAP1-AS1, LINC01137, ZSCAN16-AS1, APTR, and ELOA-AS1. This 10-CuRLs risk signature showed great diagnostic accuracy combined with traditional clinical risk factors, and a nomogram was constructed for potential clinical translation. The tumor immune microenvironment was significantly different between different risk groups. Among drugs commonly used in the treatment of lung cancer, the sensitivity of cisplatin, docetaxel, gemcitabine, gefitinib, and paclitaxel was higher in low-risk patients, and patients in the low-risk group may benefit more from imatinib.

Conclusions

These results revealed the outstanding contribution of the CuRLs signature to the evaluation of prognosis and treatment modalities for patients with LUAD. The differences in characteristics between different risk groups provide an opportunity for better patient stratification and to explore novel drugs in different risk groups.

The Characteristics of Tumor Microenvironment Predict Survival and Response to Immunotherapy in Adrenocortical Carcinomas

Increasing evidence confirms that tumor microenvironment (TME) can influence tumor progression and treatment, but TME is still understudied in adrenocortical carcinoma (ACC). In this study, we first scored TME using the xCell algorithm, then defined genes associated with TME, and then used consensus unsupervised clustering analysis to construct TME-related subtypes. Meanwhile, weighted gene co-expression network analysis was used to identify modules correlated with TME-related subtypes. Ultimately, the LASSO-Cox approach was used to establish a TME-related signature. The results showed that TME-related scores in ACC may not correlate with clinical features but do promote a better overall survival. Patients were classified into two TME-related subtypes. Subtype 2 had more immune signaling features, higher expression of immune checkpoints and MHC molecules, no CTNNB1 mutations, higher infiltration of macrophages and endothelial cells, lower tumor immune dysfunction and exclusion scores, and higher immunophenoscore, suggesting that subtype 2 may be more sensitive to immunotherapy. 231 modular genes highly relevant to TME-related subtypes were identified, and a 7-gene TME-related signature that independently predicted patient prognosis was established. Our study revealed an integrated role of TME in ACC and helped to identify those patients who really responded to immunotherapy, while providing new strategies on risk management and prognosis prediction.

Feasibility of Comprehensive Genomic Profiling (CGP) in Real-Life Clinical Practice

In advanced or metastatic settings, Comprehensive Genomic Profiling (CGP) allows the evaluation of thousands of gene alterations with the goal of offering new opportunities for personalized treatment in solid tumors. This study evaluated the CGP Success Rate in a real-life cohort of 184 patients enrolled in a prospective clinical trial. CGP data were compared with the routine molecular testing strategy adopted in-house. Sample age, tumor area, and the percentage of tumor nuclei were recorded for CGP analysis. We found that 150/184 (81.5%) samples resulted in satisfying CGP reports. The CGP Success Rate was higher in samples from surgical specimens (96.7%) and in specimens that had been stored (sample age) for less than six months (89.4%). Among the inconclusive CGP reports, 7/34 (20.6%) were optimal samples, according to CGP sample requirements. Moreover, with the in-house molecular testing approach, we could obtain clinically relevant molecular data in 25/34 (73.5%) samples that had inconclusive CGP reports. In conclusion, despite the fact that CGP offers specific therapeutical options in selected patients, our data suggest that the standard molecular testing strategy should not be replaced in routine molecular profiling.

Tumors of the Digestive System: Comprehensive Review of Ancillary Testing and Biomarkers in the Era of Precision Medicine

Immunotherapy has remained at the vanguard of promising cancer therapeutic regimens due to its exceptionally high specificity for tumor cells and potential for significantly improved treatment-associated quality of life compared to other therapeutic approaches such as surgery and chemoradiation. This is especially true in the digestive system, where high rates of mutation give rise to a host of targetable tumor-specific antigens. Many patients, however, do not exhibit measurable improvements under immunotherapy due to intrinsic or acquired resistance, making predictive biomarkers necessary to determine which patients will benefit from this line of treatment. Many of these biomarkers are assessed empirically by pathologists according to nuanced scoring criteria and algorithms. This review serves to inform clinicians and pathologists of extant and promising upcoming biomarkers predictive of immunotherapeutic efficacy among digestive system malignancies and the ancillary testing required for interpretation by pathologists according to tumor site of origin.

Association between Tumor Mutational Burden, Stromal CD8+ Tumor-Infiltrating Lymphocytes, and Clinical Factors in Cervical Cancers Treated with Radiotherapy

BACKGROUND

Tumor mutational burden (TMB) and stromal CD8-positive tumor-infiltrating lymphocytes (CD8⁺TILs) serve important roles in antitumor immune responses to radiotherapy. This study aimed to elucidate the association between TMB, CD8⁺TILs, and clinical factors in patients with cervical cancer treated with radiotherapy.

METHODS

Patients with squamous cell carcinoma of the uterine cervix treated with definitive radiotherapy, and with available somatic mutation data and immunohistochemical staining data from identical tumor tissues, were enrolled retrospectively. The association between TMB and/or CD8⁺TIL density and patient characteristics, mutation profiles, and treatment outcome was analyzed.

RESULTS

The study analyzed 44 patients (median follow-up period, 61 months). There was no significant correlation between TMB and CD8⁺TIL density, or between TMB or CD8⁺TIL density and patient characteristics. TMB-high or CD8⁺TIL density-low status was associated with worse overall survival and distant metastasis-free survival; the predictive value of these factors became greater when used in combination. TMB-high or CD8⁺TIL density-high status was associated with ARID1A mutations.

CONCLUSIONS

These data indicate independence of TMB and CD8⁺TIL density and the involvement of ARID1A alterations in antitumor immune responses in patients with cervical cancers treated with radiotherapy, warranting further mechanistic research and prospective validation.

Noninvasive evaluation of PD-L1 expression in non-small cell lung cancer by immunoPET imaging using an acylating agent-modified antibody fragment

PURPOSE

The aim of this study was to explore an effective ¹²⁴I labeling strategy and improve the signal-to-noise ratio when evaluating the expression of PD-L1 using an ¹²⁴I-iodinated durvalumab (durva) F(ab')₂ fragment.

METHODS

The prepared durva F(ab')₂ fragments were incubated with N-succinimidyl-3-(4-hydroxyphenyl) propionate (SHPP); after purification, the HPP-durva F(ab')₂ was iodinated using Iodo-Gen method. After the radiochemical purity, stability, and specific activities were determined, the binding affinities of probes prepared using different labeling strategies were compared in vitro. The clinical application value of [¹²⁴I]I-HPP-durva-F(ab')₂ was confirmed by PET imaging. To more objectively evaluate the in vivo distribution and clearance of tracers, the pharmacokinetics and biodistribution assays were also performed.

RESULTS

After being modified with SHPP, the average conjugation number of SHPP per durva-F(ab')₂ identified by LC-MS was about 8.92 ± 2.84. The prepared [¹²⁴I]I-HPP-durva F(ab')₂ was obtained with a satisfactory radiochemical purity of more than 98% and stability of more than 93% when incubated for 72 h. Compared with unmodified [¹²⁴I]I-durva F(ab')₂, the specific activity of [¹²⁴I]I-HPP-durva-F(ab')₂ was improved (52.91 ± 5.55 MBq/mg and 15.91 ± 0.74 MBq/mg), while the affinity did not significantly change. The biodistribution experiments and PET imaging showed that the prepared [¹²⁴I]I-HPP-durva-F(ab')₂ exhibited an accelerated clearance and improved tumor-to-background ratio compared with [¹²⁴I]I-durva-F(ab')₂. The specificity of [¹²⁴I]I-HPP-durva-F(ab')₂ to PD-L1 was well demonstrated both in vitro and in vivo.

CONCLUSIONS

A PD-L1 PET imaging probe [¹²⁴I]I-HPP-durva F(ab')₂ was successfully synthesized through the SHPP modification strategy. The prepared probe was able to accurately evaluate the PD-L1 expression level through high-contrast noninvasive imaging.

Genomic features and its potential implication in bone oligometastatic NSCLC

OBJECTIVES

Emerging evidence have demonstrated that oligometastatic non-small cell lung cancer (NSCLC) can achieve clinical benefit from local consolidative therapy. Bone oligometastasis is common in advanced lung cancer, but little is known about its molecular features. The purpose of our study aimed to investigate the genomic landscape bone oligometastatic NSCLC.

METHODS

We collected paired blood and tissue samples from 31 bone oligometastatic NSCLC patients to make a comprehensive analysis of mutations by performing next-generation sequencing.

RESULTS

A total of 186 genomic mutations were detected from 105 distinct cancer-relevant genes, with a median number of 6 alterations per tumor. The most frequently mutated genes were EGFR (58%) and TP53 (55%), followed by KRAS (16%), CDKN2A (13%) and MET (13%). The signatures related to smoking, aging, homologous recombination deficiency and APOBEC were identified as the most important mutational processes in bone oligometastasis. The median tumor mutation burden was 4.4 mutations/Mb. Altogether, genetic alterations of bone oligometastasis are highly targetable that 74.19% of patients had at least one actionable alteration that was recommended for targeted therapy based on the OncoKB evidence. Of these patients, 16.13% had two actionable alterations that could potentially benefit from a different combination of targeted drugs to achieve better outcomes.

CONCLUSION

Our research comprehensively elucidates the genomic features of bone oligometastatic NSCLC patients, which may optimize individualized cancer treatment in the era of precision medicine.

Neutrophil extracellular traps (NETs)-related lncRNAs signature for predicting prognosis and the immune microenvironment in breast cancer

Background: Neutrophil extracellular traps (NETs) are closely associated to tumorigenesis and development. However, the relationship between NETs-related long non-coding RNAs (lncRNAs) and the characteristics of breast tumor remains an enigma. This study aimed to explore the clinical prognostic value of NETs-related lncRNAs, their correlation with the tumor microenvironment (TME) and their predictive ability of drug sensitivity in patients with breast cancer (BC). Methods: The expression profiles of RNA-sequencing and relevant clinical data of BC patients were extracted from TCGA database. The co-expression network analysis, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were employed to construct the NETs-related lncRNAs signature. A nomogram was established and validated to explore the clinical application. Furthermore, the immune microenvironment and drug sensitivity for BC with different prognostic risks were explored. Finally, the expression pattern of lncRNAs was validated using qRT-PCR in BC tissues and their adjacent non-cancerous tissues. Results: Based on NETs-related lncRNAs, a prognostic risk model consisted of 10 lncRNAs (SFTA1P, ACTA2-AS1, AC004816.2, AC000067.1, LINC01235, LINC01010, AL133467.1, AC092919.1, AL591468.1, and MIR200CHG) was established. The Kaplan-Meier analysis showed that the overall survival (OS) was significantly better in low-risk BC patients than in high-risk BC patients (P _{training cohort} < 0.001, P _{validation cohort} = 0.009). The nomogram also showed good predictive accuracy for OS of BC individuals in both training and validation cohorts. The function enrichment analysis revealed that high-risk group was mainly enriched in immune-related functions and pathways, and the tumor mutation burden in this group was markedly higher than that in the low-risk group (p = 0.022). Moreover, significant differences were observed in immune cells, immune functions and immune checkpoint genes among BC patients at different risks (p < 0.05). The response to chemotherapeutic agents and immunotherapy were also closely related with the expression of NETs-related lncRNAs (p < 0.001). The expression of lncRNAs from experimental validation were generally consistent with the bioinformatics analysis results. Conclusion: Our study provided a novel prognostic model for BC and yielded strong scientific rationale for individualized treatment strategies, elucidating immunotherapy in BC patients.

Persistent mutation burden drives sustained anti-tumor immune responses

Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss in a pan-cancer analysis across 31 tumor types (n = 9,242) and eight immunotherapy-treated cohorts of patients with non-small-cell lung cancer, melanoma, mesothelioma, and head and neck cancer (n = 524). We discovered that mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) which is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

Evaluating Multiple Next-Generation Sequencing-Derived Tumor Features to Accurately Predict DNA Mismatch Repair Status

Identifying tumor DNA mismatch repair deficiency (dMMR) is important for precision medicine. Tumor features, individually and in combination, derived from whole-exome sequenced (WES) colorectal cancers (CRCs) and panel-sequenced CRCs, endometrial cancers (ECs), and sebaceous skin tumors (SSTs) were assessed for their accuracy in detecting dMMR. CRCs (n = 300) with WES, where mismatch repair status was determined by immunohistochemistry, were assessed for microsatellite instability (MSMuTect, MANTIS, MSIseq, and MSISensor), Catalogue of Somatic Mutations in Cancer tumor mutational signatures, and somatic mutation counts. A 10-fold cross-validation approach (100 repeats) evaluated the dMMR prediction accuracy for i) individual features, ii) Lasso statistical model, and iii) an additive feature combination approach. Panel-sequenced tumors (29 CRCs, 22 ECs, and 20 SSTs) were assessed for the top performing dMMR predicting features/models using these three approaches. For WES CRCs, 10 features provided >80% dMMR prediction accuracy, with MSMuTect, MSIseq, and MANTIS achieving ≥99% accuracy. The Lasso model achieved 98.3% accuracy. The additive feature approach, with three or more of six of MSMuTect, MANTIS, MSIseq, MSISensor, insertion-deletion count, or tumor mutational signature small insertion/deletion 2 + small insertion/deletion 7 achieved 99.7% accuracy. For the panel-sequenced tumors, the additive feature combination approach of three or more of six achieved accuracies of 100%, 95.5%, and 100% for CRCs, ECs, and SSTs, respectively. The microsatellite instability calling tools performed well in WES CRCs; however, an approach combining tumor features may improve dMMR prediction in both WES and panel-sequenced data across tissue types.

External quality assessment (EQA) for tumor mutational burden: results of an international IQN path feasibility pilot scheme

Tumor mutational burden (TMB) has recently been approved as an agnostic biomarker for immune checkpoint inhibitors. However, methods for TMB testing have not yet been standardized. The International Quality Network for Pathology (IQNPath) organized a pilot external quality assessment (EQA) scheme for TMB testing. The aim of this program was the validation of the materials and the procedures for the EQA of this complex biomarker. Five formalin-fixed paraffin-embedded (FFPE) cell lines were selected to mimic the various TMB values observed in clinical practice. The FFPE samples were tested with the FoundationOne CDx (F1CDx) assay as the reference test and three commercially available targeted sequencing panels. Following this internal validation, the five cell lines were sent to 29 laboratories selected on the basis of a previous survey. Nineteen of the 23 laboratories that submitted results (82.6%) used targeted sequencing for TMB estimation. Only two laboratories performed whole exome sequencing (WES) and two assessed TMB by clinical exome. A high variability in the reported TMB values was observed. The variability was higher for samples with the highest TMB value according to the F1CDx test. However, good reproducibility of the TMB score was shown by laboratories using the same panel. The majority of laboratories did not indicate a TMB cut-off value for clinical interpretation. In conclusion, this pilot EQA scheme suggests that it is feasible to run such an EQA program for TMB assessment. However, the results of our pilot highlight the numerous challenges for the standardization of this test.

Peripheral blood lymphocytes differentiation patterns in responses / outcomes to immune checkpoint blockade therapies in non-small cell lung cancer: a retrospective study

OBJECTIVES

Programmed Cell Death-1/ Programmed Death-ligand 1 (PD-1 / PD-L1) inhibitor therapies targeting immunocytes induce persistent tumor remission in various cancers. However, the appropriate biomarkers for the therapeutic efficacy of PD-L1 and PD-1 blockade remain elusive.

MATERIALS AND METHODS

For a comprehensive analysis of peri-treatment lymphocyte differentiation, in the current study, we enrolled 146 non-small cell lung cancer patients who received α-PD-1 therapies for exploring the peripheral blood lymphocyte differentiation pattern at baseline and post-treatment (dynamic changes) by flow cytometry.

RESULTS

At baseline, CD4⁺ / CD8⁺ T cell ratio predicts good responses and outcomes, but activated T cell and cytotoxic T cell counts predict poor responses and outcomes. And for dynamic changes, after 6 weeks of immune checkpoint blockade (ICB) treatment, compared with baseline level, the elevation of total T and B cell counts indicate poor responses, and total T and T_H cell counts indicate poor prognosis while activated T cell predicts good prognosis. And after 12 weeks, elevated total lymphocyte, cytotoxic T cell counts, and decreased total T cell counts and CD4⁺ / CD8⁺ T cell ratio predict good responses / outcomes. Our clinical predicting model shows good performance in predicting ICB treatment responses / outcomes.

CONCLUSION

Patients with favorable clinical responses / outcomes have distinctive peripheral blood immunocyte differentiation characteristics, indicating the potential of utilizing the peripheral immunocyte differentiation patterns for predicting ICB responses / outcomes.

Protein degradation: expanding the toolbox to restrain cancer drug resistance

Despite significant progress in clinical management, drug resistance remains a major obstacle. Recent research based on protein degradation to restrain drug resistance has attracted wide attention, and several therapeutic strategies such as inhibition of proteasome with bortezomib and proteolysis-targeting chimeric have been developed. Compared with intervention at the transcriptional level, targeting the degradation process seems to be a more rapid and direct strategy. Proteasomal proteolysis and lysosomal proteolysis are the most critical quality control systems responsible for the degradation of proteins or organelles. Although proteasomal and lysosomal inhibitors (e.g., bortezomib and chloroquine) have achieved certain improvements in some clinical application scenarios, their routine application in practice is still a long way off, which is due to the lack of precise targeting capabilities and inevitable side effects. In-depth studies on the regulatory mechanism of critical protein degradation regulators, including E3 ubiquitin ligases, deubiquitylating enzymes (DUBs), and chaperones, are expected to provide precise clues for developing targeting strategies and reducing side effects. Here, we discuss the underlying mechanisms of protein degradation in regulating drug efflux, drug metabolism, DNA repair, drug target alteration, downstream bypass signaling, sustaining of stemness, and tumor microenvironment remodeling to delineate the functional roles of protein degradation in drug resistance. We also highlight specific E3 ligases, DUBs, and chaperones, discussing possible strategies modulating protein degradation to target cancer drug resistance. A systematic summary of the molecular basis by which protein degradation regulates tumor drug resistance will help facilitate the development of appropriate clinical strategies.

Therapeutic landscape and future direction of metastatic colorectal cancer

In the era of targeted therapy based on genomic alterations, the treatment strategy for metastatic colorectal cancer (mCRC) has been changing. Before systemic treatment initiation, determination of tumour genomic status for KRAS and NRAS, BRAF^V600E mutations, ERBB2, and microsatellite instability and/or mismatch repair (MMR) status is recommended. In patients with deficient MMR and BRAF^V600E mCRC, randomized phase III trials have established the efficacy of pembrolizumab as first-line therapy and the combination of encorafenib and cetuximab as second-line or third-line therapy. In addition, new agents have been actively developed in other rare molecular fractions such as ERBB2 alterations and KRAS^G12C mutations. In March 2022, the combination of pertuzumab and trastuzumab for ERBB2-positive mCRC was approved in Japan, thereby combining real-world evidence from the SCRUM-Japan Registry. As the populations are highly fragmented owing to rare genomic alterations, various strategies in clinical development are expected. Clinical development of a tumour-agnostic approach, such as NTRK fusion and tumour mutational burden, has successfully introduced corresponding drugs to clinical practice. Considering the difficulty of randomized trials owing to cost-benefit and rarity, a promising solution could be real-world evidence utilized as an external control from the molecular-based disease registry.

Configuring Therapeutic Aspects of Immune Checkpoints in Lung Cancer

Immune checkpoints are unique components of the body's defense mechanism that safeguard the body from immune responses that are potent enough to harm healthy body cells. When proteins present on the surface of T cells recognize and bind to the proteins present on other tumor cells, immune checkpoints are triggered. These proteins are called immunological checkpoints. The T cells receive an on/off signal when the checkpoints interact with companion proteins. This might avert the host's immune system from eliminating cancer cells. The standard care plan for the treatment of non-small cell lung cancer (NSCLC) has been revolutionized with the use of drugs targeting immune checkpoints, in particular programmed cell death protein 1. These drugs are now extended for their potential to manage SCLC. However, it is acknowledged that these drugs have specific immune related adverse effects. Herein, we discuss the use of immune checkpoint inhibitors in patients with NSCLC and SCLC, their outcomes, and future perspectives.

Somatic Variants and Exon-Level Copy Number Changes in Five Hyperplastic Oral Leukoplakias

Oral leukoplakia (OL), an oral potentially malignant disorder, begins with a hyperplastic/hyperkeratotic stage at which no genome-scale somatic single nucleotide variant profiles have been described so far. We performed exome sequencing of five cases at this stage with no evidence of dysplasia to identify genetic alterations (exon-level copy number alterations, indels, and single nucleotide variants), their association with transcript levels, and relationship with oral cancer susceptibility. Pathway enrichment analysis of genes associated with tobacco chewing and age-related mutation signatures, transcripts with variants predicted to be functionally damaging and those with significantly altered levels all indicated the involvement of focal adhesion, ECM-receptor interactions, regulation of cytoskeleton, and DNA repair. Two novel mutations identified in FAT1 tumor suppressor gene were associated with decreased transcript levels. In addition, 16 expressed cancer driver genes contained functionally damaging variants. Many of the affected genes were also reported in dysplastic OL lesions. The presence of variants in cancer driver genes and those shared with oral dysplasias possibly provides a basis for further progression and increased susceptibility to oral cancer.

Utilizing Electronic Health Records (EHR) and Tumor Panel Sequencing to Demystify Prognosis of Cancer of Unknown Primary (CUP) patients

Cancer of unknown primary (CUP) is a type of cancer that cannot be traced back to its original site and accounts for 3-5% of all cancers. It does not have established targeted therapies, leading to poor outcomes. We developed OncoNPC, a machine learning classifier trained on targeted next-generation sequencing data from 34,567 tumors from three institutions. OncoNPC achieved a weighted F1 score of 0.94 for high confidence predictions on known cancer types (65% of held-out samples). When applied to 971 CUP tumors from patients treated at the Dana-Farber Cancer Institute, OncoNPC identified actionable molecular alterations in 23% of the tumors. Furthermore, OncoNPC identified CUP subtypes with significantly higher polygenic germline risk for the predicted cancer type and significantly different survival outcomes, supporting its validity. Importantly, CUP patients who received first palliative intent treatments concordant with their OncoNPC-predicted cancer sites had significantly better outcomes (H.R. 0.348, 95% C.I. 0.210 - 0.570, p-value 2.32 × 10-5). OncoNPC thus provides evidence of distinct CUP subtypes and offers the potential for clinical decision support for managing patients with CUP.

Identification of molecular subtypes and a prognostic signature based on chromatin regulators related genes in prostate cancer

The clinical and molecular phenotypes of prostate cancer (PCa) exhibit substantial heterogeneity, ranging from indolent to metastatic disease. In this study, we aimed to identify PCa subtypes and construct a gene signature that can predict the recurrence-free survival (RFS) of PCa patients based on chromatin regulators genes (CRGs). Strikingly, we identified two heterogeneous subtypes with distinct clinical and molecular characteristics. Furthermore, by performing differential analysis between the two CRGs subtypes, we successfully constructed a gene signature to predict PCa prognosis. The signature, comprising four genes (MXD3, SSTR1, AMH and PPFIA2), was utilized to classify PCa patients into two risk groups; the high-risk group was characterized by poor prognosis and more aggressive clinical features. Moreover, we investigated the immune profile, mutation landscape and molecular pathways in each of the groups. Additionally, drug-susceptibility testing was performed to explore sensitive drugs for high-risk patients. Furthermore, we found that MXD3 downregulation suppressed the proliferation of PCa cell lines in vitro. Overall, our results highlight the signature based on CRGs as a powerful tool for predicting RFS of PCa patients, as well as an indicator for personalized treatment of those patients.

Immunotherapy: Recent Advances and Its Future as a Neoadjuvant, Adjuvant, and Primary Treatment in Colorectal Cancer

Immunotherapy in colorectal cancer (CRC) has made great strides within the past decade. Immune checkpoint inhibitors are a class of immunotherapy and have been shown to greatly improve patient outcomes in mismatch repair-deficient (dMMR) CRC. Now, they are part of the standard of care for this subset of CRC. Because of this, there has been a growing interest in the efficacy and timing of immunotherapy for other subsets of CRC, including locally advanced, metastatic, and microsatellite stable (MSS). In this review, we aim to examine the three main classes of immunotherapy for CRC-immune checkpoint inhibitors (ICIs), adoptive cell transfer therapy (ACT), and tumor vaccines-and discuss the most recent advances and future directions for each.

Liquid biopsy approaches and immunotherapy in colorectal cancer for precision medicine: Are we there yet?

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths globally, with nearly half of patients detected in the advanced stages. This is due to the fact that symptoms associated with CRC often do not appear until the cancer has reached an advanced stage. This suggests that CRC is a cancer with a slow progression, making it curable and preventive if detected in its early stage. Therefore, there is an urgent clinical need to improve CRC early detection and personalize therapy for patients with this cancer. Recently, liquid biopsy as a non-invasive or nominally invasive approach has attracted considerable interest for its real-time disease monitoring capability through repeated sample analysis. Several studies in CRC have revealed the potential for liquid biopsy application in a real clinical setting using circulating RNA/miRNA, circulating tumor cells (CTCs), exosomes, etc. However, Liquid biopsy still remains a challenge since there are currently no promising results with high specificity and specificity that might be employed as optimal circulatory biomarkers. Therefore, in this review, we conferred the plausible role of less explored liquid biopsy components like mitochondrial DNA (mtDNA), organoid model of CTCs, and circulating cancer-associated fibroblasts (cCAFs); which may allow researchers to develop improved strategies to unravel unfulfilled clinical requirements in CRC patients. Moreover, we have also discussed immunotherapy approaches to improve the prognosis of MSI (Microsatellite Instability) CRC patients using neoantigens and immune cells in the tumor microenvironment (TME) as a liquid biopsy approach in detail.

A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma

Background: Ferroptosis is an iron-dependent cell death mode and closely linked to various cancers, including skin cutaneous melanoma (SKCM). Although attempts have been made to construct ferroptosis-related gene (FRG) signatures for predicting the prognosis of SKCM, the prognostic impact of ferroptosis-related genetic mutations in SKCM remains lacking. This study aims to develop a prediction model to explain the relationship between ferroptosis-related genetic mutations and clinical outcomes of SKCM patients and to explore the potential value of ferroptosis in SKCM treatment. Methods: FRGs which significantly correlated with the prognosis of SKCM were firstly screened based on their single-nucleotide variant (SNV) status by univariate Cox regression analysis. Subsequently, the least absolute shrinkage and selection operator (LASSO) and Cox regressions were performed to construct a new ferroptosis-related genetic mutation risk (FerrGR) model for predicting the prognosis of SKCM. We then illustrate the survival and receiver operating characteristic (ROC) curves to evaluate the predictive power of the FerrGR model. Moreover, independent prognostic factors, genomic and clinical characteristics, immunotherapy, immune infiltration, and sensitive drugs were compared between high-and low-FerrGR groups. Results: The FerrGR model was developed with a good performance on survival and ROC analysis. It was a robust independent prognostic indicator and followed a nomogram constructed to predict prognostic outcomes for SKCM patients. Besides, FerrGR combined with tumor mutational burden (TMB) or MSI (microsatellite instability) was considered as a combined biomarker for immunotherapy response. The high FerrGR group patients were associated with an inhibitory immune microenvironment. Furthermore, potential drugs target to high FerrGR samples were predicted. Conclusion: The FerrGR model is valuable to predict prognosis and immunotherapy in SKCM patients. It offers a novel therapeutic option for SKCM.

Prognostic value of tumor mutation burden in patients with advanced gastric cancer receiving first-line chemotherapy

Background

Tumor mutation burden (TMB) is a promising biomarker positively associated with the benefit of immunotherapy and that might predict the outcome of chemotherapy. We described the prognostic value of TMB in advanced gastric cancer and explored the underlying mechanism.

Methods

We enrolled 155 TMB-evaluated advanced gastric cancer patients and analyzed the relationship between clinicopathological characteristics and both overall survival (OS) and progression-free survival (PFS) among 40 patients treated with first-line chemotherapy. We further verified the distribution of TMB and analyzed the potential mechanism underlying the prognosis based on The Cancer Genome Atlas (TCGA) database.

Results

Among the 155 patients, 29 (18.7%) were TMB-high (TMB ≥ 10), roughly the same as the proportion in the TCGA data. Of the 40 patients receiving first-line chemotherapy, the median OS (7.9 vs. 12.1 months; HR 3.18; p = 0.0056) and PFS (4.4 vs. 6.2 months; HR 2.94; p = 0.0099) of the tissue-tested TMB (tTMB)-high patients were inferior to those of the tTMB-low patients. Similarly, unfavorable median OS (9.9 vs. 12.1 months; HR 2.11; p = 0.028) and PFS (5.3 vs. 6.5 months; HR 2.49; p = 0.0054) were shown in the blood-tested TMB (bTMB)-high than in the bTMB-low patients. The Cox analysis demonstrated that both tTMB-high and bTMB-high were significant independent predictors of dreadful OS and PFS. The differentially expressed genes (DEGs) according to TMB status were most significantly enriched in the downregulated metabolic pathway among the TMB-high patients.

Conclusions

TMB-high advanced gastric cancer patients accounted for around one-sixth and had a poorer prognosis than TMB-low patients when treated with first-line chemotherapy. The potential mechanism might be the downregulated metabolic activity in TMB-high patients.

Characterization of Leukemic Resistance to CD19-Targeted CAR T-cell Therapy through Deep Genomic Sequencing

Chimeric antigen receptor (CAR) T-cell therapy targeting CD19 has been a clinical breakthrough for pediatric B-cell acute lymphoblastic leukemia (B-ALL), and loss of the CD19 target antigen on leukemic cells represents a major mechanism of relapse. Previous studies have observed CD19 mutations specific to CD19- relapses, and we sought to clarify and strengthen this relationship using deep whole-exome sequencing in leukemic cells expanded in a patient-derived xenograft. By assessing pre-treatment and relapse cells from 13 patients treated with CAR T-cell therapy, 8 of whom developed CD19- relapse and 5 of whom developed CD19+ relapse, we demonstrate that relapse-specific single-nucleotide variants and small indels with high allele frequency combined with deletions in the CD19 gene in a manner specific to those patients with CD19- relapse. Before CAR T-cell infusion, one patient was found to harbor a pre-existing CD19 deletion in the context of genomic instability, which likely represented the first hit leading to the patient's subsequent CD19- relapse. Across patients, preexisting mutations and genomic instability were not significant predictors of subsequent CD19- relapse across patients, with sample size as a potential limiting factor. Together, our results clarify and strengthen the relationship between genomic events and CD19- relapse, demonstrating this intriguing mechanism of resistance to a targeted cancer immunotherapy.

Pretreatment Serum Lactate Dehydrogenase and Metastases Numbers as Potential Determinants of Anti-PD-1 Therapy Outcome in Nasopharyngeal Carcinoma

BACKGROUND

We aimed to investigate the determinant factors of anti-PD-1 therapy outcome in nasopharyngeal carcinoma (NPC).

METHODS

In this retrospective study, we included 64 patients with recurrent/metastatic NPC. The association of patients' characteristics, C-reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), and lactate dehydrogenase (LDH) with survival benefit of anti-PD-1 therapy were analyzed using Cox regression models and Kaplan-Meier analyses. Patients were divided based on the median value of CRP, NLR or LDH into different subgroups.

RESULTS

At a median follow-up time of 11.4 months (range: 1-28 months), median progression-free survival (PFS) and overall survival (OS) were 1.9 months (95% CI, .18-3.6) and 15 months (95% CI, 10.9-19.1) months, respectively. Pretreatment metastases numbers was significant predictor of PFS (HR = 1.99; 95% CI 1.10-3.63; P = .024) and OS (HR = 2.77; 95% CI 1.36-5.61; P = .005). Baseline LDH level was independent predictor of OS (HR = 7.01; 95% CI 3.09-15.88; P < .001). Patients with LDH level >435 U/L at the baseline had significantly shorter PFS and OS compared to patients with LDH level ≤435 U/L (median PFS: 1.7 vs 3.5 months, P = .040; median OS: 3.7 vs 18.5 months, P < .001). Patients with non-durable clinical benefit (NDB) had significantly higher LDH level at the baseline compared to patients who achieved durable clinical benefit (DCB) (P = .025). Post-treatment levels of CRP, LDH, and NLR were decreased compared to baseline in patients with DCB (P = .030, P = .088, and P = .066, respectively), whereas, there was a significant increase in post-treatment level of LDH compared with baseline in patients with NDB (P = .024).

CONCLUSIONS

LDH level at the baseline was an independent predictor of OS and pretreatment metastases numbers was a significant predictor of PFS and OS.

Identification of an m6A-related lncRNA prognostic signature in colorectal cancer

Data sets of colorectal cancer (CRC) were obtained from The Cancer Genome Atlas (TCGA), three N6-methyladenosine (m6A) subtypes were identified using 21 m6A-related long noncoding RNAs (lncRNAs) and differential m6A subtypes of different CRC tumors were determined in this study to evaluate the m6A expression and the prognosis of patients with CRC. Subsequently, eight key lncRNAs were identified based on co-expression with 21 m6A-related genes in CRC tumors using the single-factor Cox and least absolute shrinkage and selection operator. Finally, an m6A-related lncRNA risk score model of CRC tumor was established using multifactor Cox regression based on the eight important lncRNAs and found to have a better performance in evaluating the prognosis of patients in the TCGA-CRC data set. TCGA-CRC tumor samples were divided based on the risk scores: high and low. Then, the clinical characteristics, tumor mutation load, and tumor immune cell infiltration difference between the high- and low-risk-score groups were explored, and the predictive ability of the risk score was assessed for immunotherapeutic benefits. We found that the risk score model can determine the overall survival, be a relatively independent prognostic indicator, and better evaluate the immunotherapeutic benefits for patients with CRC. This study provides data support for accurate immunotherapy in CRC.

Unveiling DNA damage repair-based molecular subtypes, tumor microenvironment and pharmacogenomic landscape in gastric cancer

Objective: The current molecular classification system for gastric cancer covers genomic, molecular, and morphological characteristics. Non-etheless, classification of gastric cancer based upon DNA damage repair is still lacking. Here, we defined DNA damage repair-based subtypes across gastric cancer and identified clinicopathological, tumor microenvironment and pharmacogenomic features. Methods: Unsupervised clustering analysis was executed in the TCGA-STAD cohort based upon the transcriptional expression profiling of DNA damage repair genes. LASSO computational approach was adopted for generating a DNA damage repair-relevant gene signature. The identified subtypes or signature were externally verified in the GSE84426 or GSE84433 cohort. The transcriptional levels of immunomodulators, abundance of immune cells and somatic mutations were measured, respectively. Immunotherapeutic response, and drug sensitivity were investigated. The DNA damage repair-relevant genes were further experimentally verified. Results: Two DNA damage repair-based subtypes were identified, with the notable heterogeneity in prognostic stratification, tumor microenvironment and somatic mutations. The gene signature was generated for risk stratification and prognostic prediction, which was in relation to immunomodulators and immune cells. High-risk cases were more likely to respond to immunotherapy, with distinct pharmacogenomic landscapes between low- and high-risk groups. Higher levels of PAPPA2, MPO, MAGEA11, DEPP1, CPZ, and COLEC12 and lower level of CYTL1 were proven in gastric cancer cells versus controls. Silencing CYTL1 facilitated intracellular ROS accumulation and suppressed migration in gastric cancer cells. Conclusion: Collectively, the DNA damage repair-based classification is a suitable complement to existing molecular classification system, and the quantitative gene signature provides a robust tool in selecting specific therapeutic options.

Dissection of tumor antigens and immune landscape in clear cell renal cell carcinoma: Preconditions for development and precision medicine of mRNA vaccine

Accumulating evidence reveals that mRNA-type cancer vaccines could be exploited as cancer immunotherapies in various solid tumors. However, the use of mRNA-type cancer vaccines in clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to identify potential tumor antigens for the development of an anti-ccRCC mRNA vaccine. In addition, this study aimed to determine immune subtypes of ccRCC to guide the selection of patients to receive the vaccine. Raw sequencing and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Further, the cBioPortal website was used to visualize and compare genetic alterations. GEPIA2 was employed to evaluate the prognostic value of preliminary tumor antigens. Moreover, the TIMER web server was used to evaluate correlations between the expression of specific antigens and the abundance of infiltrated antigen-presenting cells (APCs). Single-cell RNA sequencing data of ccRCC was used to explore the expression of potential tumor antigens at single-cell resolution. The immune subtypes of patients were analyzed by the consensus clustering algorithm. Furthermore, the clinical and molecular discrepancies were further explored for a deep understanding of the immune subtypes. Weighted gene co-expression network analysis (WGCNA) was used to cluster the genes according to the immune subtypes. Finally, the sensitivity of drugs commonly used in ccRCC with diverse immune subtypes was investigated. The results revealed that the tumor antigen, LRP2, was associated with a good prognosis and enhanced the infiltration of APCs. ccRCC could be divided into two immune subtypes (IS1 and IS2) with distinct clinical and molecular characteristics. The IS1 group showed a poorer overall survival with an immune-suppressive phenotype than the IS2 group. Additionally, a large spectrum of differences in the expression of immune checkpoints and immunogenic cell death modulators were observed between the two subtypes. Lastly, the genes correlated with the immune subtypes were involved in multiple immune-related processes. Therefore, LRP2 is a potential tumor antigen that could be used to develop an mRNA-type cancer vaccine in ccRCC. Furthermore, patients in the IS2 group were more suitable for vaccination than those in the IS1 group.

NALCN is a potential biomarker and therapeutic target in human cancers

Background: Sodium leak channel non-selective (NALCN), known as a voltage-independent Na⁺ channel, is increasingly considered to play vital roles in tumorigenesis and metastasis of human cancers. However, no comprehensive pan-cancer analysis of NALCN has been conducted. Our study aims to explore the potential diagnostic, prognostic and therapeutic value of NALCN in human cancers. Methods: Through comprehensive application of datasets from Human Protein Atlas (HPA), The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Enhanced Version of Tumor Immune Estimation Resource (TIMER2.0), Tumor and Immune System Interaction Database (TISIDB), The University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), cBioPortal, GeneMANIA and Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) databases, we explored the potential roles of NALCN in different cancers. The differential expression, prognostic implications, pathological stages and grades, molecular and immune subtypes, diagnostic accuracy, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, immune checkpoint genes, chemokine genes, major histocompatibility complex (MHC)-related genes, tumor-infiltrating immune cells (TIICs), promoter methylation, mutations, copy number alteration (CNA), and functional enrichment related to NALCN were analyzed. Results: Most cancers lowly expressed NALCN. Upregulated NALCN expression was associated with poor or better prognosis in different cancers. Moreover, NALCN was correlated with clinicopathological features in multiple cancers. NALCN showed high diagnostic accuracy in 5 caner types. NALCN is highly linked with immune-related biomarkers, immune-related genes and TIICs. Significant methylation changes and genetic alteration of NALCN can be observed in many cancers. Enrichment analysis showed that NALCN is closely related to multiple tumor-related signaling pathways. Conclusion: Our study revealed the vital involvement of NALCN in cancer. NALCN can be used as a prognostic biomarker for immune infiltration and clinical outcomes, and has potential diagnostic and therapeutic implications.

Identification of tumor antigens and immune landscapes for bladder urothelial carcinoma mRNA vaccine

Background

Bladder urothelial carcinoma (BLCA) is associated with high mortality and recurrence. Although mRNA-based vaccines are promising treatment strategies for combating multiple solid cancers, their efficacy against BLCA remains unclear. We aimed to identify potential effective antigens of BLCA for the development of mRNA-based vaccines and screen for immune clusters to select appropriate candidates for vaccination.

Methods

Gene expression microarray data and clinical information were retrieved from The Cancer Genome Atlas and GSE32894, respectively. The mRNA splicing patterns were obtained from the SpliceSeq portal. The cBioPortal for Cancer Genomics was used to visualize genetic alteration profiles. Furthermore, nonsense-mediated mRNA decay (NMD) analysis, correlation analysis, consensus clustering analysis, immune cell infiltration analysis, and weighted co-expression network analysis were conducted.

Results

Six upregulated and mutated tumor antigens related to NMD, and infiltration of APCs were identified in patients with BLCA, including HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2. The patients were subdivided into two immune clusters (IC1 and IC2) with distinct clinical, cellular and molecular features. Patients in IC1 represented immunologically 'hot' phenotypes, whereas those in IC2 represented immunologically 'cold' phenotypes. Moreover, the survival rate was better in IC2 than in IC1, and the immune landscape of BLCA indicated significant inter-patient heterogeneity. Finally, CALD1, TGFB3, and ANXA6 were identified as key genes of BLCA through WGCNA analysis, and their mRNA expression levels were measured using qRT-PCR.

Conclusion

HP1BP3, OSBPL9, SSH3, ZCCHC8, FANCI, and EIF4A2 were identified as potential antigens for developing mRNA-based vaccines against BLCA, and patients in IC2 might benefit more from vaccination.

A pan-cancer analysis of ABI3BP: a potential biomarker for prognosis and immunoinfiltration

Objective

ABI Family Member 3 Binding Protein (ABI3BP) is an extracellular matrix protein that affects the carcinogenesis of lung and esophageal cancer. However, the relevance of ABI3BP in different forms of cancer is uncertain.

Methods

ABI3BP expression was interpreted using the Cancer Genome Atlas (TCGA) database, the Genotype Tissue Expression Atlas (GTEx) database, the Human Protein Atlas (HPA) database, the Cancer Cell Line Encyclopedia (CCLE) database, and immunohistochemistry. The R programming language was used to analyze the association between ABI3BP expression and patient prognosis and evaluate the relationship between ABI3BP and the immune characteristics of tumors. Using the GDSC and CTRP databases, a drug sensitivity analysis of ABI3BP was conducted.

Results

ABI3BP mRNA expression was shown by differential analysis to be down-regulated in 16 tumor types relative to normal tissues, corresponding with its protein expression level as determined by immunohistochemistry. Abnormal expression of ABI3BP accurately predicts the prognosis of patients with renal chromophobe carcinoma (KICH), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD). Meanwhile, aberrant expression of ABI3BP was associated with immune checkpoints, TMB, MSI, tumor purity, HRD, LOH, and drug sensitivity. A correlation between ABI3BP expression and the amount of infiltration of several immune-related cells in pan-cancer was determined by Immune Score, Stromal Score, and Estimated Score.

Conclusion

Our results show that ABI3BP might be employed as a molecular biomarker to predict prognosis, treatment susceptibility, and immunological response in patients with pan-cancer.

Pathology of neoadjuvant therapy and immunotherapy testing for breast cancer

Neoadjuvant chemotherapy (NACT) has become the standard of care for high-risk breast cancer, including triple-negative (TNBC) and HER2-positive disease. As a result, handling and reporting of breast specimens post-NACT is part of routine practice, and it is important for pathologists to recognise the changes in tumour cells, tumour-associated stroma and background breast tissue induced by NACT. Familiarity with characteristic stromal features enables identification of the pre-treatment tumour site and allows confident diagnosis of pathological complete response (pCR) which is important for decisions concerning adjuvant therapy. Neoadjuvant endocrine therapy (NAET) is used less frequently than NACT; however, the SARS-COVID-19 pandemic has changed practice, with increased use as bridging therapy if surgery is delayed. NAET also induces characteristic changes in the tumour and stroma. Changes in the tumour microenvironment following NACT and NAET are also described. Immunotherapy is approved for use in advanced TNBC, and there are several trials exploring its role in early TNBC in the neoadjuvant setting. The current biomarker to determine eligibility for treatment with immune checkpoint inhibitors is programmed death ligand-1 (PD-L1) immunohistochemistry; however, this is complicated by lack of standardisation with different drugs linked to tests using different antibodies with different scoring systems. The situation in the neoadjuvant setting is further complicated by improved pCR rates for PD-L1-positive tumours in both immune therapy and placebo arms. Alternative biomarkers are urgently needed to identify which patients will derive benefit from immunotherapy and key candidates are discussed.

Amphipathic barbiturates as marine product mimics with cytolytic and immunogenic effects on head and neck squamous cell carcinoma cell lines

The incidence of head and neck squamous cell carcinoma (HNSCC) is increasing and the conventional treatments for this form of cancer can be tough. Despite the success of existing immunotherapies in some HNSCC patients, many do not respond to this type of treatment. Thus, the development of novel anti-cancer therapies should be prioritized. In the current study, the anticancer activity of a panel of novel compounds, herein termed marine product mimics (MPMs), against HNSCC cell lines is explored. The previously reported compound MPM-1, which is structurally related to the novel MPMs, was shown to have promising effects on the HNSCC cell line HSC-3. The results from the current study indicate that the novel MPMs are more potent than MPM-1 but cause a similar type of cell death. The results indicated that the MPMs must cross through the cell membrane to exert their action and that they are lysosomotropic. Further experiments showed that some of the MPMs could induce phosphorylation of eukaryotic initiation factor 2α (eIF2α) in HSC-3 and UT-SCC-24A cells, which indicates that they can activate the integrated stress response that is strongly associated with immunogenic cell death. Cell surface expression of calreticulin and release of HMGB1 and ATP, which are all hallmarks of immunogenic cell death, was also demonstrated in HSC-3 and UT-SCC-24A cells treated with MPMs. This suggests that the MPMs are interesting candidates for future HNSCC cancer therapies.

Involvement of CHRNA6 in the Immune Response in Lung Squamous Cell Carcinoma and its Potential as a Drug Target for the Disease

BACKGROUND

Lung squamous cell carcinoma (LUSC) is a subtype of lung cancer with a poor prognosis and limited treatment options. Previous studies show that some components of the cholinergic pathway may play important roles in the tumorigenesis of lung cancer, including LUSC.

OBJECTIVE

The purpose of this study is to investigate the involvement of cholinergic genes in immune infiltration in LUSC, and identify the key genes in the pathway and analyze their potential as targets for LUSC treatment and novel drugs.

METHODS

We first screened the cholinergic genes associated with immune infiltration in LUSC based on transcriptomic samples and explored the correlation between the key genes and immune infiltrating cells and immune pathways. Then, we assessed the effect of immunotherapeutic response in the high and low-expression groups of key genes in vitro. And finally, we screened potential drugs for the treatment of LUSC.

RESULTS

We found that the expression of CHRNA6, the gene encoding the α6 subunit of nicotinic acetylcholine receptors (nAChR), was significantly correlated with the proportion of immune infiltrating cells in LUSC, and the high expression level of the gene was associated with poor prognosis of the disease. Also, the proportion of Tregs, M1 macrophages, and resting mast cells was correlated with the expression of CHRNA6. In addition, LUSC patients with higher CHRNA6 expression levels had better immunotherapy responses. Furthermore, we found that the drugs, i.e., adavosertib, varbulin and pyrazoloacridine, had a strong affinity with CHRNA6, with adavosertib binding most stably with the protein.

CONCLUSION

CHRNA6 may be associated with immune infiltration in LUSC and affects patient prognosis and immunotherapeutic response by regulating immune cells and immune pathways. In addition, adavosertib may be a potential drug for the treatment of LUSC.

Novel immunogenic cell death-related risk signature to predict prognosis and immune microenvironment in lung adenocarcinoma

PURPOSE

Immunogenic cell death (ICD) is a type of regulated cell death (RCD) which was discovered to activate adaptive immunity. To date, the effect of ICD on lung adenocarcinoma (LUAD) remains unclear. In this research, we will study the role of ICD-related genes (ICDG) in LUAD.

METHODS

RNA sequencing and clinical data were gathered from TCGA-LUAD cohorts and GEO database. Using unsupervised cluster analysis, three clusters were identified with distinctive immune characteristics and significant overall survival based on 18 ICDG. Using LASSO Cox regression, three genes were identified and used to construct the prognosis signature. The association between the 3-ICDG risk signature and immune microenvironment analysis, somatic mutation, and enriched molecular pathways was investigated.

RESULTS

Consensus clustering separated the LUAD samples into three clusters (ICDcluster A, B and C), and ICDcluster B had the best prognosis. Different TME cell infiltration characteristics and biological behavior were found in three ICD clusters. Prognostic risk model was contrasted based on the 3 best prognostic ICD-related genes. Subsequently, vitro experiments verified the above analysis results. The high-risk group showed a poor prognosis and enrichment of cancer promoting signal pathway. Multivariate analysis indicated that this 3-ICDG prognostic model might be an accurate prediction parameter for LUAD. Moreover, conducting immune related analysis, we found that the 3-ICDG risk signature was characterized by an immune-active subtype on account of the high infiltration of immune-active cells.

CONCLUSION

This study expands our cognition of ICD in LUAD microenvironment, excavated prognostic biomarkers, and provided potential value for guiding immunotherapy and chemotherapy.

Tislelizumab Versus Docetaxel in Patients With Previously Treated Advanced NSCLC (RATIONALE-303): A Phase 3, Open-Label, Randomized Controlled Trial

INTRODUCTION

The phase 3 RATIONALE-303 trial (NCT03358875) investigated the efficacy and safety of tislelizumab versus docetaxel in pretreated patients with advanced NSCLC. Here, we report the efficacy and safety results and describe the exploratory biomarker analyses.

METHODS

A total of 805 patients aged more than or equal to 18 years with locally advanced or metastatic squamous or nonsquamous NSCLC were randomized 2:1 to intravenous tislelizumab 200 mg or docetaxel 75 mg/m² every 3 weeks. Co-primary end points were overall survival (OS) in the intent-to-treat (ITT) and programmed death-ligand 1 (PD-L1) tumor cell expression greater than or equal to 25% populations. The exploratory biomarker analyses included PD-L1 expression, tumor mutation burden, and gene expression profile.

RESULTS

At the prespecified interim analysis (August 10, 2020), the co-primary end point of OS in the ITT population was met, with a statistically significant and clinically meaningful improvement in OS with tislelizumab versus docetaxel (median 17.2 versus 11.9 mo, respectively; hazard ratio [HR] = 0.64, p < 0.0001). At the final analysis (July 15, 2021), the other co-primary end point of OS in the PD-L1 tumor cell greater than or equal to 25% population was further met (median 19.3 versus 11.5 mo, respectively; HR = 0.53, p < 0.0001), and OS continued to improve in the ITT population (median 16.9 versus 11.9 mo, respectively, HR = 0.66). Exploratory biomarker analyses revealed the potential association of NOTCH1-4 mutations with improved tislelizumab efficacy for both OS and progression-free survival, whereas tissue tumor mutation burden correlated with progression-free survival benefit, but not OS benefit. No new safety signals were identified.

CONCLUSIONS

Tislelizumab was found to have a significantly improved and long-term clinical benefit in OS versus docetaxel in pretreated patients with advanced NSCLC, regardless of PD-L1 expression.

Prognostic and Immunological Implications of FAM72A in Pan-Cancer and Functional Validations

The family with sequence similarity 72 Member A (FAM72A) is overexpressed in several types of cancer. However, its contributions to tumorigenesis remain largely unknown. Based on The Cancer Genome Atlas (TCGA) database, FAM72A was upregulated across 33 types of cancer. Accordingly, high levels of FAM72A predicted inferior outcomes in half of the cancer types using survival analysis (the Kaplan-Meier curve and univariate Cox regression model). Receiver operating characteristic (ROC) analysis demonstrated that FAM72A showed high accuracy in distinguishing cancerous tissues from normal ones. FAM72A was correlated with immune and stromal scores and immune cell infiltrations in various tumors. Moreover, FAM72A was also associated with tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint genes. Immunophenoscore (IPS) further validated that the FAM72A^low tumor showed high immunogenicity and tended to respond to anti-PD1/PDL1/PDL2, anti-CTLA4 treatment, and combined immunotherapies. We also investigated the functional role of FAM72A in lung adenocarcinoma (LUAD). In vitro studies demonstrated that the ectopic expression of FAM72A accelerated the proliferation and migration of NSCLC cells, whereas silencing FAM72A showed the opposite effects on them. In short, FAM72A had prognostic potential and correlated with tumor immunogenicity in various tumors. Functional analysis indicated that FAM72A is an oncogene in LUAD.

Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy

BACKGROUND

Immune checkpoint blockades (ICBs) have emerged as a promising treatment for cancer. Recently, tumour mutational burden (TMB) and neoantigen load (NAL) have been proposed to be potential biomarkers to predict the efficacy of ICB; however, they were limited by difficulties in defining the cut-off values and inconsistent detection platforms. Therefore, it is critical to identify more effective predictive biomarkers for screening patients who will potentially benefit from immunotherapy. In this study, we aimed to identify comutated signaling pathways to predict the clinical outcomes of immunotherapy.

METHODS

Here, we comprehensively analysed the signaling pathway mutation status of 9763 samples across 33 different cancer types from The Cancer Genome Atlas (TCGA) by mapping the somatic mutations to the pathways. We then explored the comutated pathways that were associated with increased TMB and NAL by using receiver operating characteristic (ROC) curve analysis and multiple linear regressions.

RESULTS

Our results revealed that comutation of the Spliceosome (Sp) pathway and Hedgehog (He) signaling pathway (defined as SpHe-comut⁺) could be used as a predictor of increased TMB and NAL and was associated with increased levels of immune-related signatures. In seven independent immunotherapy cohorts, we validated that SpHe-comut⁺ patients exhibited a longer overall survival (OS) or progression-free survival (PFS) and a higher objective response rate (ORR) than SpHe-comut^- patients. Moreover, a combination of SpHe-comut status with PD-L1 expression further improved the predictive value for ICB therapy.

CONCLUSION

Overall, SpHe-comut⁺ was demonstrated to be an effective predictor of immunotherapeutic benefit in seven independent immunotherapy cohorts and may serve as a potential and convenient biomarker for the clinical application of ICB therapy.

ANK2 as a novel predictive biomarker for immune checkpoint inhibitors and its correlation with antitumor immunity in lung adenocarcinoma

BACKGROUND

Immune checkpoint inhibitors (ICIs) have been shown to significantly improve the survival of patients with advanced lung adenocarcinoma (LUAD). However, only limited proportion of patients could benefit from ICIs. Novel biomarkers with strong predictability are needed for clinicians to maximize the efficacy of ICIs. Our study aimed to identify potential biomarkers predicting ICIs efficacy in LUAD.

METHODS

The Cancer Genome Atlas (TCGA) PanCancer Atlas studies in cBioportal were used to evaluate the mutation frequency of ANK2 across multiple cancers. Clinical and mutational data for LUAD from ICIs-treated cohorts (Hellmann et al. and Rizvi et al.) were collected to explore the correlation between ANK2 mutation and clinical outcomes. In addition, the relationship between ANK2 expression and clinical outcomes was analyzed using LUAD data from TCGA and Gene Expression Omnibus. Furthermore, the impact of ANK2 mutation and expression on the tumor immune microenvironment of LUAD was analyzed using TCGA and TISIDB databases.

RESULTS

Patients with ANK2 mutation benefited more from ICIs. In ICIs-treated cohort, prolonged progression-free survival (PFS) (median PFS: NR (not reached) vs. 5.42 months, HR (hazard ratio) 0.31, 95% CI 0.18-0.54; P = 0.0037), improved complete response rate (17.65% vs. 1.85%, P = 0.0402), and improved objective response rate (64.71% vs. 24.07%, P = 0.0033) were observed in LUAD patients with ANK2 mutation compared to their wild-type counterparts. Regarding ANK2 expression, it was observed that ANK2 expression was decreased in LUAD (P < 0.05) and a higher level of ANK2 expression was associated with longer overall survival (HR 0.69, 95% CI 0.52-0.92; P = 0.012) in TCGA LUAD cohort. Moreover, ANK2 mutation or higher ANK2 expression correlated with enhanced antitumor immunity and "hot" tumor microenvironment in LUAD, which could be potential mechanisms that ANK2 mutation facilitated ICIs therapy and patients with higher ANK2 expression survived longer.

CONCLUSION

Our findings suggest that ANK2 mutation or increased ANK2 expression may serve as a favorable biomarker for the efficacy of ICIs in patients with LUAD.

Lung Cancer Immunotherapy: Beyond Common Immune Checkpoints Inhibitors

Immunotherapy is an ever-expanding field in lung cancer treatment research. Over the past two decades, there has been significant progress in identifying immunotherapy targets and creating specific therapeutic agents, leading to a major paradigm shift in lung cancer treatment. However, despite the great success achieved with programmed death protein 1/ligand 1 (PD-1/PD-L1) monoclonal antibodies and with anti-PD-1/PD-L1 plus anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4), only a minority of lung cancer patients respond to treatment, and of these many subsequently experience disease progression. In addition, immune-related adverse events sometimes can be life-threatening, especially when anti-CTLA-4 and anti-PD-1 are used in combination. All of this prompted researchers to identify novel immune checkpoints targets to overcome these limitations. Lymphocyte activation gene-3 (LAG-3), T cell immunoglobulin (Ig) and Immunoreceptor Tyrosine-Based Inhibitory Motif (ITIM) domain (TIGIT), T cell immunoglobulin and mucin-domain containing-3 (TIM-3) are promising molecules now under investigation. This review aims to outline the current role of immunotherapy in lung cancer and to examine efficacy and future applications of the new immune regulating molecules.

Sintilimab plus autologous NK cells as second-line treatment for advanced non-small-cell lung cancer previous treated with platinum-containing chemotherapy

This pilot study (NCT03958097; https://www.clinicaltrials.gov/ct2/show/NCT03958097) was aimed to evaluate the efficacy and safety of PD-1 antibody combined autologous NK cells in the treatment of patients with stage IIIB/IIIC or IV non-small-cell lung cancer (NSCLC) who failed the first-line platinum-based chemotherapy. All patients received both sintilimab 200mg and 3×10⁹ NK cells every 3 weeks. 20 patients were enrolled, median follow up time was 22.6 months. The median PFS was 11.6 months, ORR was 45%. Median OS was 17.7 months, 6-month OS rate and 12-month OS rate was 95.0% and 80.0%. Unexpected adverse events were not observed. 2 patients reported grade 3 adverse events (hypertriglyceridemia, neutropenia and increased creatine kinase). The autologous NK cells did not add extra adverse events to the ICI treatment. Autologous NK plus sintilimab showed promising antitumor activity and an acceptable safety profile in advanced driven-mutation negative NSCLC who failed on the first line treatment.

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

Introduction

Breast cancer is a heterogeneous tumor. Tumor microenvironment (TME) has an important effect on the proliferation, metastasis, treatment, and prognosis of breast cancer.

Methods

In this study, we calculated the relative proportion of tumor infiltrating immune cells (TIICs) in the breast cancer TME, and used the consensus clustering algorithm to cluster the breast cancer subtypes. We also developed a multi-layer perceptron (MLP) classifier based on a deep learning framework to detect breast cancer subtypes, which 70% of the breast cancer research cohort was used for the model training and 30% for validation.

Results

By performing the K-means clustering algorithm, the research cohort was clustered into two subtypes. The Kaplan-Meier survival estimate analysis showed significant differences in the overall survival (OS) between the two identified subtypes. Estimating the difference in the relative proportion of TIICs showed that the two subtypes had significant differences in multiple immune cells, such as CD8, CD4, and regulatory T cells. Further, the expression level of immune checkpoint molecules (PDL1, CTLA4, LAG3, TIGIT, CD27, IDO1, ICOS) and tumor mutational burden (TMB) also showed significant differences between the two subtypes, indicating the clinical value of the two subtypes. Finally, we identified a 38-gene signature and developed a multilayer perceptron (MLP) classifier that combined multi-gene signature to identify breast cancer subtypes. The results showed that the classifier had an accuracy rate of 93.56% and can be robustly used for the breast cancer subtype diagnosis.

Conclusion

Identification of breast cancer subtypes based on the immune signature in the tumor microenvironment can assist clinicians to effectively and accurately assess the progression of breast cancer and formulate different treatment strategies for different subtypes.

Identifying tumor antigens and immuno-subtyping in colon adenocarcinoma to facilitate the development of mRNA vaccine

The mRNA vaccine has provided a promising approach for cancer immunotherapies. However, only a few mRNA vaccines have been developed against colon adenocarcinoma (COAD). Screening potential targets for mRNA vaccines from numerous candidates is a substantial challenge. Considering the tumor heterogeneity, only a subset of patients might respond to vaccinations. This study was conducted to identify potential candidates for mRNA vaccines, and distinguish appropriate subgroups of COAD patients for vaccination. A total of five tumor antigens with prognostic values were identified, including IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5. The COAD patients were stratified into five immune subtypes (IS1-IS5), according to consensus clustering analysis. Higher tumor mutation burden (TMB) was observed in IS1 and IS5 subtypes. The IS1 and IS5 subtypes have shown the baseline of immune-hot tumor microenvironment, while other subtypes displayed immune desert phenotype. Distinct expressions of immune checkpoints (ICPs)-related genes and immunogenic cell death (ICD) modulators were observed among five immune subtypes. Finally, the immune landscape was conducted to narrow the immune components for better personalized mRNA-based vaccination. The IFIT3, PARP9, TAP1, STAT1, and OAS2 were confirmed as hub genes, and COAD patients with higher expressions of these genes might be more appropriate for mRNA vaccination. In conclusion, the IGF2BP3, DPCR1, HOXD10, TRIM7, and ZIC5 were identified as potential candidates for developing mRNA vaccines against COAD, and patients in IS1 and IS5 subtypes might respond better to mRNA vaccination.

Epigenetic Mechanisms Underlying Melanoma Resistance to Immune and Targeted Therapies

Melanoma is an aggressive skin cancer reliant on early detection for high likelihood of successful treatment. Solar UV exposure transforms melanocytes into highly mutated tumor cells that metastasize to the liver, lungs, and brain. Even upon resection of the primary tumor, almost thirty percent of patients succumb to melanoma within twenty years. Identification of key melanoma genetic drivers led to the development of pharmacological BRAF^V600E and MEK inhibitors, significantly improving metastatic patient outcomes over traditional cytotoxic chemotherapy or pioneering IFN-α and IL-2 immune therapies. Checkpoint blockade inhibitors releasing the immunosuppressive effects of CTLA-4 or PD-1 proved to be even more effective and are the standard first-line treatment. Despite these major improvements, durable responses to immunotherapy and targeted therapy have been hindered by intrinsic or acquired resistance. In addition to gained or selected genetic alterations, cellular plasticity conferred by epigenetic reprogramming is emerging as a driver of therapy resistance. Epigenetic regulation of chromatin accessibility drives gene expression and establishes distinct transcriptional cell states. Here we review how aberrant chromatin, transcriptional, and epigenetic regulation contribute to therapy resistance and discuss how targeting these programs sensitizes melanoma cells to immune and targeted therapies.

Identification of tumor antigens and immune subtypes in head and neck squamous cell carcinoma for mRNA vaccine development

The mRNA vaccines have been considered effective for combating cancer. However, the core components of the mRNA vaccines against head and neck squamous cell carcinoma (HNSCC) and the effects remain unclear. Our study aims to identify effective antigens in HNSCC to develop mRNA vaccines for corresponding potential patients. Here, we analyzed alternative splicing and mutation of genes in TCGA-HNSCC samples and identified seven potential tumor antigens, including SREBF1, LUC7L3, LAMA5, PCGF3, HNRNPH1, KLC4, and OFD1, which were associated with nonsense-mediated mRNA decay factor expression, overall survival prognosis and the infiltration of antigen-presenting cells. Furthermore, to select suitable patients for vaccination, immune subtypes related to HNSCC were identified by consensus clustering analysis, and visualization of the HNSCC immune landscape was performed by graph-learning-based dimensionality reduction. To address the heterogeneity of the population that is suitable for vaccination, plot cell trajectory and WGCNA were also utilized. HNSCC patients were classified into three prognostically relevant immune subtypes (Cluster 1, Cluster 2, and Cluster 3) possessing different molecular and cellular characteristics, immune modulators, and mutation statuses. Cluster 1 had an immune-activated phenotype and was associated with better survival, while Cluster 2 and Cluster 3 were immunologically cold and linked to increased tumor mutation burden. Therefore, HNSCC patients with immune subtypes Cluster 2 and Cluster 3 are potentially suitable for mRNA vaccination. Moreover, the prognostic module hub genes screened seven genes, including IGKC, IGHV3-15, IGLV1-40, IGLV1-51, IGLC3, IGLC2, and CD79A, which could be potential biomarkers to predict prognosis and identify suitable patients for mRNA vaccines. Our findings provide a theoretical basis for further research and the development of anti-HNSCC mRNA vaccines and the selection of suitable patients for vaccination.

Genomic and Transcriptomic Predictors of Response to Immune Checkpoint Inhibitors in Melanoma Patients: A Machine Learning Approach

Immune checkpoint inhibitors (ICIs) became one of the most revolutionary cancer treatments, especially in melanoma. While they have been proven to prolong survival with lesser side effects compared to chemotherapy, the accurate prediction of response remains to be an unmet gap. Thus, we aim to identify accurate clinical and transcriptomic biomarkers for ICI response in melanoma. We also provide mechanistic insight into how high-performing markers impose their effect on the tumor microenvironment (TME). Clinical and transcriptomic data were retrieved from melanoma studies administering ICIs from cBioportal and GEO databases. Four machine learning models were developed using random-forest classification (RFC) entailing clinical and genomic features (RFC7), differentially expressed genes (DEGs, RFC-Seq), survival-related DEGs (RFC-Surv) and a combination model. The xCELL algorithm was used to investigate the TME. A total of 212 ICI-treated melanoma patients were identified. All models achieved a high area under the curve (AUC) and bootstrap estimate (RFC7: 0.71, 0.74; RFC-Seq: 0.87, 0.75; RFC-Surv: 0.76, 0.76, respectively). Tumor mutation burden, GSTA3, and VNN2 were the highest contributing features. Tumor infiltration analyses revealed a direct correlation between upregulated genes and CD8+, CD4+ T cells, and B cells and inversely correlated with myeloid-derived suppressor cells. Our findings confirmed the accuracy of several genomic, clinical, and transcriptomic-based RFC models, that could further support the use of TMB in predicting response to ICIs. Novel genes (GSTA3 and VNN2) were identified through RFC-seq and RFC-surv models that could serve as genomic biomarkers after robust validation.