Tumor mutational burden on cytological samples: A pilot study

Head and Neck Fine Needle Aspiration: Current and Future Impact on Patient Care

The discovery of multiple novel biomarkers in head and neck tumors has led to an increasing interest in utilizing head and neck cytology material as the primary specimens for testing diagnostic and prognostic biomarkers. Although human papillomavirus and programmed death ligand 1 are the most well-established biomarkers tested in cytology specimens, their utilization in cytology is limited by the absence of standardized protocols for specimen collection and fixation. This has led to a quest for innovative techniques to explore the genomic landscape in head and neck tumors and its application in cytology.

Pulmonary Cytopathology: Current and Future Impact on Patient Care

Small biopsies of lung are routinely obtained by many methods, including several that result in cytologic specimens. Because lung cancer is often diagnosed at a stage for which primary resection is not an option, it is critical that all diagnostic, predictive, and prognostic information be derived from such small biopsy specimens. As the number of available diagnostic and predictive markers expands, cytopathologists must familiarize themselves with current requirements for specimen acquisition, handling, results reporting, and molecular and other ancillary testing, all of which are reviewed here.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Efficacy of cross-line anti-programmed death 1/programmed cell death-ligand 1 antibody in the treatment of advanced nonsmall cell lung cancer: A retrospective study

Background and Aims

Immune checkpoint inhibitors (ICIs) across multiple treatment lines have not yet been evaluated comprehensively. The purpose of this research was to investigate whether or not continuous cross-line ICIs therapy is effective in treating non-small cell lung cancer (NSCLC).

Methods

We conducted a retrospective investigation into the medical histories of 47 patients diagnosed with advanced NSCLC and treated with ICIs at the Peking University First Hospital between January 2018 and June 2022.

Results

Due to the progression of their disease, 14 patients were given the same ICIs, 5 patients were given different ICIs, and 6 patients discontinued taking ICIs altogether. The objective response rates were 7.140% in the ICIs cross-line treatment group, 0% in the replacement of ICIs treatment group, and 0% in the discontinuation of ICIs treatment group. The disease control rates were 64.260% in the ICIs cross-line treatment group, 60% in the replacement of ICIs treatment group, and 0% in the discontinuation of ICIs treatment group. The average overall survival durations of the three groups were 24.020 (95% confidence interval [CI]: 17.061-30.979), 31.643 (95% CI: 23.513-39.774), and 7.997 (95% CI: 3.746-12.247) months, respectively (p = 0.003). The median second progression-free survival (PFS2) durations of the three groups were 4.570 (95% CI: 3.276-5.864), 3.530 (95% CI: 0.674-6.386), and 1.570 (95% CI: 0-4.091) months, respectively (p = 0.091).

Conclusions

Cross-line ICIs cannot improve the prognosis and PFS2 of patients with NSCLC, but compared to discontinuing ICIs, OS may be prolonged. A few patients may benefit from prolonged ICIs therapy.

Performance of non-formalin fixed paraffin embedded samples in hybrid capture and amplicon next-generation sequencing panels

BACKGROUND

Genomic profiling using next-generation sequencing (NGS) is fundamental for driving prognostic and therapy in cancer. Formalin-fixed paraffin embedded (FFPE) tissue is the widely used material, whereas non-FFPE may represent an alternative. However, studies comparing the NGS performance of non-FFPE materials to FFPE are still lacking in the literature. The objective of this study was to characterize in non-FFPE preparations the nucleic acid yield and NGS performance on both a capture-based and an amplicon-based NGS platform. NGS quality metrics obtained from non-FFPE preparations were compared to FFPE.

METHODS

We analyzed the cellularity and nucleic acid yield in 111 tumors from non-FFPE preparations. In addition, comprehensive hybrid capture panel sequencing metrics obtained from DNA and RNA libraries were compared between independent non-FFPE and FFPE samples. A paired comparison between non-FFPE and FFPE samples was performed to analyze concordance in mutant allele detection using an amplicon panel.

RESULTS

The mean target coverage from DNA libraries was 2× higher in non-FFPE samples than in FFPE. The detection of exogenous DNA was 2.5× higher in non-FFPE than in FFPE. Conversely, a lower performance was observed in non-FFPE RNA libraries in comparison to FFPE DNA libraries with no impact in minimum standard cutoffs. The variant allele detection in non-FFPE was found to be comparable to that of FFPE tumor samples in matched samples.

CONCLUSIONS

Non-FFPE was demonstrated to be a suitable material for DNA and RNA library preparations using a comprehensive NGS panel. This is the first study reporting library quality metrics according to the TSO500 analysis pipeline.

Genomic profiling of tissue and blood predicts survival outcomes in patients with resected pleural mesothelioma

PURPOSE

Pleural mesothelioma (PM) is an aggressive tumor still considered incurable, in part due to the lack of predictive biomarkers. Little is known about the clinical implications of molecular alterations in resectable PM tissues and blood. Here, we characterized genetic alterations to identify prognostic and predictive biomarkers in patients with resected PM.

EXPERIMENTAL DESIGN

Targeted next-generation sequencing was performed in retrospective pleural tumor tissue and paired plasma samples from stage IB-IIIB resected PM. Association between prognosis and presence of specific mutations was validated in silico.

RESULTS

Thirty PM tissues and paired blood samples from 12 patients were analyzed. High tissue tumor mutational burden (TMB) (>10 mutations/Mb), tissue median minor allele frequency (MAF) (>9 mutations/Mb), and blood TMB (>6 mutations/Mb), tissue KMT2C, PBRM1, PKHD1,EPHB1 and blood LIFR mutations correlated with longer disease-free survival and/or overall survival. High concordance (>80%) between tissue and blood was found for some mutations.

CONCLUSIONS

Tissue TMB and MAF, blood TMB, and specific mutations correlated with outcomes in patients with resected PM and should be further studied to validate their role as prognostic biomarkers and potentially predictive factors for combinations with immune-checkpoint inhibitors. This suggest that molecular profiling could identify longer survivors in patients with resected PM.

Discrepancies in tumor mutation burden reporting from sequential endobronchial ultrasound transbronchial needle aspiration samples within single lymph node stations - brief report

Introduction

Tumour Mutation Burden (TMB) is a potential biomarker for immune cancer therapies. Here we investigated parameters that might affect TMB using duplicate cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes.

Methods

Individual Diff-Quik cytology smears were prepared for each needle pass. DNA extracted from each smear underwent sequencing using large gene panel (TruSight Oncology 500 (TSO500 - Illumina)). TMB was estimated using the TSO500 Local App v. 2.0 (Illumina).

Results

Twenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average smear TMB was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB (scores below or above a threshold of 10 mutations/Mb). Markedly discrepant TMB was observed in four cases, with an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling included sample tumour content, the amount of DNA used in sequencing, and bone fide heterogeneity of node tumour between paired samples.

Conclusion

TMB assessment is feasible from EBUS-TBNA smears from a single needle pass. Repeated samples of a lymph node station have minimal variation in TMB in most cases. However, this novel data shows how tumour content and minor change in site of node sampling can impact TMB. Further study is needed on whether all node aspirates should be combined in 1 sample, or whether testing independent nodes using smears is needed.

Network approach in liquidomics landscape

Tissue-based biopsy is the present main tool to explore the molecular landscape of cancer, but it also has many limits to be frequently executed, being too invasive with the risk of side effects. These limits and the ability of cancer to constantly evolve its genomic profile, have recently led to the need of a less invasive and more accurate alternative, such as liquid biopsy. By searching Circulating Tumor Cells and residues of their nucleic acids or other tumor products in body fluids, especially in blood, but also in urine, stools and saliva, liquid biopsy is becoming the future of clinical oncology. Despite the current lack of a standardization for its workflows, that makes it hard to be reproduced, liquid biopsy has already obtained promising results for cancer screening, diagnosis, prognosis, and risk of recurrence.Through a more accessible molecular profiling of tumors, it could become easier to identify biomarkers predictive of response to treatment, such as EGFR mutations in non-small cell lung cancer and KRAS mutations in colorectal cancer, or Microsatellite Instability and Mismatch Repair as predictive markers of pembrolizumab response.By monitoring circulating tumor DNA in longitudinal repeated sampling of blood we could also predict Minimal Residual Disease and the risk of recurrence in already radically resected patients.In this review we will discuss about the current knowledge of limitations and strengths of the different forms of liquid biopsies for its inclusion in normal cancer management, with a brief nod to their newest biomarkers and its future implications.

Immunotherapy efficacy predictive tool for lung adenocarcinoma based on neural network

Background

Remarkably, the anti-cancer efficacy of immunotherapy in lung adenocarcinoma (LUAD) has been demonstrated. However, predicting the beneficiaries of this expensive treatment is still a challenge.

Materials and methods

A group of patients (N = 250) diagnosed with LUAD and receiving immunotherapy were retrospectively studied. They were randomly divided into a training dataset (80%) and a test dataset (20%). The training dataset was utilized to train neural network models to predict patients’ objective response rate (ORR), disease control rate (DCR), responders (progression-free survival time > 6 months), and overall survival (OS) possibility, which were validated by both the training and test datasets and packaged into a tool later.

Results

In the training dataset, the tool scored 0.9016 area under the receiver operating characteristic (AUC) curve on ORR judgment, 0.8570 on DCR, and 0.8395 on responder prediction. In the test dataset, the tool scored 0.8173 AUC on ORR, 0.8244 on DCR, and 0.8214 on responder determination. As for OS prediction, the tool scored 0.6627 AUC in the training dataset and 0.6357 in the test dataset.

Conclusions

This immunotherapy efficacy predictive tool for LUAD patients based on neural networks could predict their ORR, DCR, and responder well.

Reference standards for gene fusion molecular assays on cytological samples: an international validation study

AIMS

Gene fusions assays are key for personalised treatments of advanced human cancers. Their implementation on cytological material requires a preliminary validation that may make use of cell line slides mimicking cytological samples. In this international multi-institutional study, gene fusion reference standards were developed and validated.

METHODS

Cell lines harbouring EML4(13)-ALK(20) and SLC34A2(4)-ROS1(32) gene fusions were adopted to prepare reference standards. Eight laboratories (five adopting amplicon-based and three hybridisation-based platforms) received, at different dilution points two sets of slides (slide A 50.0%, slide B 25.0%, slide C 12.5% and slide D wild type) stained by Papanicolaou (Pap) and May Grunwald Giemsa (MGG). Analysis was carried out on a total of 64 slides.

RESULTS

Four (50.0%) out of eight laboratories reported results on all slides and dilution points. While 12 (37.5%) out of 32 MGG slides were inadequate, 27 (84.4%) out of 32 Pap slides produced libraries adequate for variant calling. The laboratories using hybridisation-based platforms showed the highest rate of inadequate results (13/24 slides, 54.2%). Conversely, only 10.0% (4/40 slides) of inadequate results were reported by laboratories adopting amplicon-based platforms.

CONCLUSIONS

Reference standards in cytological format yield better results when Pap staining and processed by amplicon-based assays. Further investigation is required to optimise these standards for MGG stained cells and for hybridisation-based approaches.

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade

Different biomarkers based on genomics variants have been used to predict the response of patients treated with PD-1/programmed death receptor 1 ligand (PD-L1) blockade. We aimed to use deep-learning algorithm to estimate clinical benefit in patients with non-small-cell lung cancer (NSCLC) before immunotherapy. Peripheral blood samples or tumor tissues of 915 patients from three independent centers were profiled by whole-exome sequencing or next-generation sequencing. Based on convolutional neural network (CNN) and three conventional machine learning (cML) methods, we used multi-panels to train the models for predicting the durable clinical benefit (DCB) and combined them to develop a nomogram model for predicting prognosis. In the three cohorts, the CNN achieved the highest area under the curve of predicting DCB among cML, PD-L1 expression, and tumor mutational burden (area under the curve [AUC] = 0.965, 95% confidence interval [CI]: 0.949–0.978, P< 0.001; AUC =0.965, 95% CI: 0.940–0.989, P< 0.001; AUC = 0.959, 95% CI: 0.942–0.976, P< 0.001, respectively). Patients with CNN-high had longer progression-free survival (PFS) and overall survival (OS) than patients with CNN-low in the three cohorts. Subgroup analysis confirmed the efficient predictive ability of CNN. Combining three cML methods (CNN, SVM, and RF) yielded a robust comprehensive nomogram for predicting PFS and OS in the three cohorts (each P< 0.001). The proposed deep-learning method based on mutational genes revealed the potential value of clinical benefit prediction in patients with NSCLC and provides novel insights for combined machine learning in PD-1/PD-L1 blockade.

Accuracy of next-generation sequencing for molecular profiling of small specimen of lung cancer: a prospective pilot study of side-by-side comparison

Background

Successful practice of precision medicine in advanced lung cancers relies on therapeutic regimens tailored to individual molecular characteristics. The aim of this study was to investigate the accuracy of small specimens for molecular profiling using next-generation sequencing (NGS).

Methods

Genetic alternations, tumor mutational burden (TMB), status of microsatellite instability (MSI), and expression of programmed death ligand 1 (PD-L1) were compared side-by-side between the concurrently obtained core needle biopsy (CNB) and resection specimens in 17 patients with resectable non-small cell lung cancers.

Results

DNA yield and library complexity were significantly lower in CNB specimens (both p < 0.01), whereas the insert size, sequencing depth, and Q30 ratio were similar between the matched specimens (all p > 0.05). The total numbers of genetic alternations detected in resection and CNB specimens were 186 and 211, respectively, with 156 alternations in common, yielding a specific concordance rate of 83.9%. The prevalence of mutations in 8 major driver genes was 100% identical between surgical and CNB specimens, though the allele frequency was lower in CNB specimens, with a median underestimation of 57%. Results of TMB were similar (p = 0.547) and MSI status was 100% matched in all paired specimens.

Conclusions

Pulmonary CNB specimens were suitable for NGS given the satisfactory accuracy when compared to corresponding surgical specimens. NGS results yielding from CNB specimens should be deemed reliable to provide instructive information for the treatment of advanced lung cancers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13000-022-01255-y.

N6-Methyladenosine (m6A)-Related lncRNAs Are Potential Signatures for Predicting Prognosis and Immune Response in Lung Squamous Cell Carcinoma

Background

Despite increasing understanding of m⁶A-related lncRNAs in lung cancer, the role of m⁶A-related lncRNAs in the prognosis and treatment of lung squamous cell carcinoma is poorly understood to date. Thus, the current study aims to elucidate its role and build a model to predict the prognosis of LUSC patients.

Materials and Methods

The data of the current study were accessed from the TCGA database. Pearson correlation analysis was performed to identify lncRNAs correlated to m⁶A. Next, an m⁶A-related lncRNAs risk model was built using a single factor, least absolute association, selection operator, and multivariate Cox regression analysis.

Results

The relevance between 23 m⁶A genes and 14,056 lncRNAs is shown by Pearson correlation analysis by Sankey diagram. Multivariate Cox regression analysis determined that 11 m⁶A-lncRNAs show predictive potential in prognosis, which is confirmed by the consistency index, Kaplan–Meier analysis, principal component analysis, and ROC curve. Additionally, the immune analysis showed that the enrichment of immune cells, major histocompatibility complex molecules, and immune checkpoints in the high and low-risk subgroups were markedly disparate, with the high-risk group showing a stronger immune escape ability and a worse response to immunotherapy.

Conclusion

In conclusion, the risk model based on m⁶A-related lncRNAs showed great promise in predicting the prognosis and the efficacy of immunotherapy.

Increased Tumor Intrinsic Growth Potential and Decreased Immune Function Orchestrate the Progression of Lung Adenocarcinoma

Background

The overall 5-year survival of lung cancer was reported to be only ~15%, with lung adenocarcinoma (LUAD) as the main pathological subtype. Before developing into invasive stages, LUAD undergoes pre-invasive stages of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), where surgical resection gives an excellent 5-year survival rate. Given the dramatic decline of prognosis from pre-invasive to invasive stages, a deeper understanding of key molecular changes driving the progression of LUAD is highly needed.

Methods

In this study, we performed whole-exome sequencing and RNA sequencing on surgically resected 24 AIS, 74 MIA, 99 LUAD specimens, and their adjacent paired normal tissues. Survival data were obtained by follow-up after surgery. Key molecular events were found by comparing the gene expression profiles of tumors with different stages. Finally, to measure the level of imbalance between tumor intrinsic growth potential and immune microenvironment, a tumor progressive (TP) index was developed to predict tumor progression and patients’ survival outcome and validated by external datasets.

Results

As tumors progressed to more invasive stages, they acquired higher growth potential, mutational frequency of tumor suppressor genes, somatic copy number alterations, and tumor mutation burden, along with suppressed immune function. To better predict tumor progression and patients’ outcome, TP index were built to measure the imbalance between tumor intrinsic growth potential and immune microenvironment. Patients with a higher TP index had significantly worse recurrence-free survival [Hazard ratio (HR), 10.47; 95% CI, 3.21–34.14; p < 0.0001] and overall survival (OS) [Hazard ratio (HR), 4.83e8; 95% CI, 0–Inf; p = 0.0013]. We used The Cancer Genome Atlas (TCGA)-LUAD dataset for validation and found that patients with a higher TP index had significantly worse OS (HR, 1.10; 95% CI, 0.83–1.45; p = 0.048), demonstrating the prognostic value of the TP index for patients with LUAD.

Conclusions

The imbalance of tumor intrinsic growth potential and immune function orchestrate the progression of LUAD, which can be measured by TP index. Our study provided new insights into predicting survival of patients with LUAD and new target discovery for LUAD through assessing the imbalance between tumor intrinsic growth potential and immune function.

Accuracy of whole slide image based image analysis is adversely affected by preanalytical factors such as stained tissue slide and paraffin block age

Background

Personalized medicine and accurate quantification of tumor and biomarker expression have become the cornerstone of cancer diagnostics. This requires Quality Control (QC) of research tissue samples to confirm adequate targeted tumor tissue sampling. Digitalization of stained tissue slides offer a precious way to archive, preserve, and retrieve necessary information when needed. This study is aimed to assess the most significant pre-analytic and analytic factors that might contribute to the efficacy of obtaining accurate whole slide images (WSIs) interpretation. Various studies are needed to identifysuch factors to allow for appropriate AI application and adequate tumor area/percentage quantification.

Methods

Hematoxylene and Eosine (H&E) satined WSIs collected from tissue specimens provided by the Cooperative Human Tissue Network (CHTN) Midwestern Division (CHTNMWD) were analyzed. Tissue specimens were processed, fixed, stained, and scanned contemporaneously (within 1 month). Two cohorts of malignant, colorectal cancer, 20X WSI (ScanscopeXT, Leica Biosystems, Illinois), were assembled. The study identified a "recent cohort" that included 76 WSIs created on 2018 or later. "Aged cohort" included 73 WSIs from specimens procured in the period of (2012-2014). Twenty recent WSIs of adenocarcinoma cases were used to construct WSIs analysis algorithms (VIS, Visiopharm A/S, Denmark) using machine learning to produce morphometric maps and calculate tissue and tumor areas.

Results

Algorithmic analysis of 69 WSIs from rescanned aged slides vs. that of contemporaneous WSIs concluded 18 (28%) similar finding in tumor areas (within 10%), 56 (82%) had identicaltissue areas, and 54 (79%) had similar tumor percentages.

Conclusion

WSIs of aged H&E slides and stained paraffin block re-cuts produce different tumor quantification compared to those of original scanned sslides most likely due to pre-analytical factors. The difference in tumor area detected between original and rescanned WSIs trended upward in the period between 2012 and 2014. Less tumor area was detected as the slides age. Recut and H&E-stained tissues from stored paraffin blocks may detect more tumor due to excess eosinophilia. These results highlights the value of documenting archives of H&E WSIs collected at the procurement time. Such images provide a superior archive over glass slides and Formalin-Fixed Paraffin-Embedded (FFPE) blocks and contribute betterg to WSIs analysis application.

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.

A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts Tumor Immune Profiles in Non-Small Cell Lung Cancer: A Retrospective Multicohort Study

Background

The tumor immune microenvironment (TIME) phenotypes have been reported to mainly impact the efficacy of immunotherapy. Given the increasing use of immunotherapy in cancers, knowing an individual's TIME phenotypes could be helpful in screening patients who are more likely to respond to immunotherapy. Our study intended to establish, validate, and apply a machine learning model to predict TIME profiles in non-small cell lung cancer (NSCLC) by using 18F-FDG PET/CT radiomics and clinical characteristics.

Methods

The RNA-seq data of 1145 NSCLC patients from The Cancer Genome Atlas (TCGA) cohort were analyzed. Then, 221 NSCLC patients from Daping Hospital (DPH) cohort received18F-FDG PET/CT scans before treatment and CD8 expression of the tumor samples were tested. The Artificial Intelligence Kit software was used to extract radiomic features of PET/CT images and develop a radiomics signature. The models were established by radiomics, clinical features, and radiomics-clinical combination, respectively, the performance of which was calculated by receiver operating curves (ROCs) and compared by DeLong test. Moreover, based on radiomics score (Rad-score) and clinical features, a nomogram was established. Finally, we applied the combined model to evaluate TIME phenotypes of NSCLC patients in The Cancer Imaging Archive (TCIA) cohort (n = 39).

Results

TCGA data showed CD8 expression could represent the TIME profiles in NSCLC. In DPH cohort, PET/CT radiomics model outperformed CT model (AUC: 0.907 vs. 0.861, P = 0.0314) to predict CD8 expression. Further, PET/CT radiomics-clinical combined model (AUC = 0.932) outperformed PET/CT radiomics model (AUC = 0.907, P = 0.0326) or clinical model (AUC = 0.868, P = 0.0036) to predict CD8 expression. In the TCIA cohort, the predicted CD8-high group had significantly higher immune scores and more activated immune pathways than the predicted CD8-low group (P = 0.0421).

Conclusion

Our study indicates that 18F-FDG PET/CT radiomics-clinical combined model could be a clinically practical method to non-invasively detect the tumor immune status in NSCLCs.

Cell-Free Tumor DNA (cf-tDNA) Liquid Biopsy: Current Methods and Use in Brain Tumor Immunotherapy

Gliomas are tumors derived from mutations in glial brain cells. Gliomas cause significant morbidity and mortality and development of precision diagnostics and novel targeted immunotherapies are critically important. Radiographic imaging is the most common technique to diagnose and track response to treatment, but is an imperfect tool. Imaging does not provide molecular information, which is becoming critically important for identifying targeted immunotherapies and monitoring tumor evolution. Furthermore, immunotherapy induced inflammation can masquerade as tumor progression in images (pseudoprogression) and confound clinical decision making. More recently, circulating cell free tumor DNA (cf-tDNA) has been investigated as a promising biomarker for minimally invasive glioma diagnosis and disease monitoring. cf-tDNA is shed by gliomas into surrounding biofluids (e.g. cerebrospinal fluid and plasma) and, if precisely quantified, might provide a quantitative measure of tumor burden to help resolve pseudoprogression. cf-tDNA can also identify tumor genetic mutations to help guide targeted therapies. However, due to low concentrations of cf-tDNA, recovery and analysis remains challenging. Plasma cf-tDNA typically represents <1% of total cf-DNA due to the blood-brain barrier, limiting their usefulness in practice and motivating the development and use of highly sensitive and specific detection methods. This mini review summarizes the current and future trends of various approaches for cf-tDNA detection and analysis, including new methods that promise more rapid, lower-cost, and accessible diagnostics. We also review the most recent clinical case studies for longitudinal disease monitoring and highlight focus areas, such as novel accurate detection methodologies, as critical research priorities to enable translation to clinic.

Inhibitors of PD-1 in Non-Small Cell Lung Cancer: A Meta-Analysis of Clinical and Molecular Features

Objective

PD-1 inhibitors have become an indispensable treatment in Non-Small Cell Lung Cancer (NSCLC), but the potential predictive value of clinical and molecular features need to be clarified. The objective of the study was to study the potency of PD-1 inhibitors in patients with NSCLC in contexts of both clinical and molecular features, and to aid identification of patients for choice of type of PD-1 inhibitor therapy in order to acquire more accurate NSCLC treatment in immunotherapy.

Method

PubMed, Google Scholar, Embase Science Direct, the Cochrane library, and major oncology conferences were searched for randomized clinical trials (RCTs) that were published prior to December 2021. RCTs that had PD-1 inhibitor alone or in combination with chemotherapy with non-PD-1 inhibitor for the treatment of NSCLC patients were selected. Two authors independently selected studies, data extraction and bias risk assessment. Basic characteristics of included studies, and also the 95% confidence interval and hazard ratios of the overall patients and subgroups were recorded. The inverse variance weighted method was used to estimate pooled treatment data.

Result

A total of eleven RCTs including 5,887 patients were involved. PD-1 inhibitors-based therapy substantially enhanced OS compared with non-PD-1 inhibitor therapy in patients with age group <65 years, 65-74 years, active or previous smokers, without brain metastases, liver metastases, EGFR wild-type patients, individuals in East Asia and U.S./Canada, but not in patients with age group ≥75 years, never smokers, brain metastases, EGFR mutant patients or individuals in Europe. OS was improved in patients with NSCLC who received PD-1 inhibitors regardless of their gender (male or female), histomorphological subtypes (squamous or non-squamous NSCLC), performance status (0 or 1), and PD-L1 tumor proportion score (TPS) (<1%, ≥1%, 1-49%, or ≥50%). An analysis of subgroups revealed that, patients with age group <65 years old, male, non squamous cell carcinoma, PS 1, TPS ≥1%, and TPS ≥50% benefited from pembrolizumab treatment not related with treatment line and treatment regimen.

Conclusion

Age group, smoking history, metastasis status/site, EGFR mutation status, and region can be used to predict the potency of PD-1 inhibitors, and to be individualized to choose different types of PD-1 inhibitors, and treatment regimen for NSCLC patients.

Real-world application of tumor mutational burden-high (TMB-high) and microsatellite instability (MSI) confirms their utility as immunotherapy biomarkers

Introduction

Microsatellite instability (MSI) testing and tumor mutational burden (TMB) are genomic biomarkers used to identify patients who are likely to benefit from immune checkpoint inhibitors. Pembrolizumab was recently approved by the Food and Drug Administration for use in TMB-high (TMB-H) tumors, regardless of histology, based on KEYNOTE-158. The primary objective of this retrospective study was real-world applicability and use of immunotherapy in TMB/MSI-high patients to lend credence to and refine this biomarker.

Methods

Charts of patients with advanced solid tumors who had MSI/TMB status determined by next generation sequencing (NGS) (FoundationOne CDx) were reviewed. Demographics, diagnosis, treatment history, and overall response rate (ORR) were abstracted. Progression-free survival (PFS) was determined from Kaplan–Meier curves. PFS1 (chemotherapy PFS) and PFS2 (immunotherapy PFS) were determined for patients who received immunotherapy after progressing on chemotherapy. The median PFS2/PFS1 ratio was recorded.

Results

MSI-high or TMB-H [≥20 mutations per megabase (mut/MB)] was detected in 157 adults with a total of 27 distinct tumor histologies. Median turnaround time for NGS was 73 days. ORR for most recent chemotherapy was 34.4%. ORR for immunotherapy was 55.9%. Median PFS for patients who received chemotherapy versus immunotherapy was 6.75 months (95% confidence interval, 3.9-10.9 months) and 24.2 months (95% confidence interval, 9.6 months to not reached), respectively (P = 0.042). Median PFS2/PFS1 ratio was 4.7 in favor of immunotherapy.

Conclusion

This real-world study reinforces the use of TMB as a predictive biomarker. Barriers exist to the timely implementation of NGS-based biomarkers and more data are needed to raise awareness about the clinical utility of TMB. Clinicians should consider treating TMB-H patients with immunotherapy regardless of their histology.

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This retrospective study examined the real-world use of immune checkpoint inhibitors (ICIs) in TMB/MSI-high patients with a diverse set of cancer types.

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TMB is an emerging tumor-agnostic biomarker for response to treatment with ICIs that may expand personalized cancer care.

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ICIs remain underutilized as a first-line therapy for TMB/MSI-H patients without specific histologic approval for ICIs.

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The PFS2 to PFS1 ratio was 4.7, favoring immunotherapy over chemotherapy even as a second-line therapy.

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Our study reinforces the real-world evidence that TMB is a valid surrogate marker for MSI and can predict response to ICIs.

Tissue Microarray from Cell Block Material (cbTMA)—An Additional Shot for Cytology in the Predictive Pathology Era: The PD-L1 Experience

Generally, predictive biomarker tests are clinically validated on histological formalin-fixed, paraffin-embedded (FFPE) samples. In addition to FFPE samples, cytological samples have also emerged as a useful approach to detect predictive biomarkers. However, as of today, despite the promising results reported in the recent literature, their full implementation in routine clinical practice is still lagging owing to a lack of standardized preparatory protocols, challenging assessments of cyto-histological correlation, and variable inter-observer agreement. The aim of this report was to explore the possibility of implementing a large-scale validation of predictive biomarker testing on cytological material. To this aim, we evaluated the technical feasibility of PD-L1 assessment on a cell block (CB)-derived tissue microarray (cbTMA). Consecutive and unselected CBs prepared from metastatic lymph node fine-needle cytology (FNC) samples were retrospectively collected and used for TMA construction. PD-L1 immunohistochemistry (IHC) was carried out on cbTMA sections with the companion diagnostic kit SP263 assay. TMA contained 33 CB-derived cores. A total of 20 sections were hematoxylin and eosin (H&E) stained. Overall, 29 (88%) samples were visible at least in one H&E-stained slide. Four cases out of five sections stained with the SP263 assay (4/29, 13.8%) showed PD-L1 positivity in neoplastic and/or immune cells; remarkably, no unspecific background was observed. Although our study was based on a limited and non-selected series, our findings do provide proof of concept for the use of cbTMA in predictive biomarker testing on cytological material in large-scale post-clinical trial validation studies, multicenter studies, and quality control programs.

Tumor mutation burden for predicting immune checkpoint blockade response: the more, the better

BACKGROUND

Recently, the US Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) for treating cancer patients with tumor mutation burden (TMB) >10 mutations/megabase (mut/Mb). However, high TMB (TMB-H) defined by >10 mut/Mb fails to predict ICB response across different cancer types, which has raised serious concerns on the current FDA approval. Thus, to better implement TMB as a robust biomarker of ICB response, an optimal and generalizable TMB cut-off within and across cancer types must be addressed as soon as possible.

METHODS

Using Morris's and Kurzrock's cohorts (n=1662 and 102), we exhaustively tested all possible TMB cut-offs for predicting ICB treatment outcomes in 10 cancer types. The bootstrap method was applied to generate 10,000 randomly resampled cohorts using original cohorts to measure the reproducibility of TMB cut-off. ICB treatment outcomes were analyzed by overall survival, progression-free survival and objective response rate.

RESULTS

No universally valid TMB cut-off was available for all cancer types. Only in cancer types with higher TMB (category I), such as melanoma, colorectal cancer, bladder cancer, and non-small cell lung cancer, the associations between TMB-H and ICB treatment outcomes were less affected by TMB cut-off selection. Moreover, high TMB (category I) cancer types shared a wide range of TMB cut-offs and a universally optimal TMB cut-off of 13 mut/Mb for predicting favorable ICB outcomes. In contrast, low TMB (category II) cancer types, for which the prognostic associations were sensitive to TMB cut-off selection, showed markedly limited and distinct ranges of significantly favorable TMB cut-offs. Equivalent results were obtained in the analyses of pooled tumors.

CONCLUSIONS

Our finding-the correlation that TMB-H is more robustly associated with favorable ICB treatment outcomes in cancer types with higher TMBs-can be used to predict whether TMB could be a robust predictive biomarker in cancer types for which TMB data are available, but ICB treatment has not been investigated. This theory was tested in cancer of unknown primary successfully. Additionally, the universal TMB cut-off of 13 mut/Mb might reveal a general requirement to trigger the sequential cascade from somatic mutations to an effective antitumor immunity.

Assessment of the albumin-bilirubin grade as a prognostic factor in patients with non-small-cell lung cancer receiving anti-PD-1-based therapy

Introduction

The albumin-bilirubin (ALBI) grade is a novel indicator of the liver function. Some studies showed that the ALBI grade was a prognostic and predictive biomarker for the efficacy of chemotherapy in cancer patients. The association between the ALBI grade and outcomes in patients with non-small-cell lung cancer (NSCLC) treated with cancer immunotherapy, however, is poorly understood.

Methods

We retrospectively enrolled 452 patients with advanced or recurrent NSCLC who received anti-programmed cell death protein 1 (PD-1)-based therapy between 2016 and 2019 at three medical centers in Japan. The ALBI score was calculated from albumin and bilirubin measured at the time of treatment initiation and was stratified into three categories, ALBI grade 1-3, with reference to previous reports. We examined the clinical impact of the ALBI grade on the outcomes of NSCLC patients receiving anti-PD-1-based therapy using Kaplan–Meier survival curve analysis with log-rank test and Cox proportional hazards regression analysis.

Results

The classifications of the 452 patients were as follows: grade 1, n = 158 (35.0%); grade 2, n = 271 (60.0%); and grade 3, n = 23 (5.0%). Kaplan–Meier survival curve analysis showed that the ALBI grade was significantly associated with progression-free survival and overall survival. Moreover, Cox regression analysis revealed that the ALBI grade was an independent prognostic factor for progression-free survival and overall survival.

Conclusion

The ALBI grade was an independent prognostic factor for survival in patients with advanced or recurrent NSCLC who receive anti-PD-1-based therapy. These findings should be validated in a prospective study with a larger sample size.

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ALBI grade is calculated from albumin and bilirubin.

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We evaluated the impact of ALBI grade on survival in NSCLC patients receiving immune checkpoint inhibitors.

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ALBI grade was an independent prognostic factor for progression-free survival (PFS) and overall survival (OS).

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ALBI grade effectively stratified PFS and OS in patients with performance status 1-3.

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ALBI grade was significantly associated with PFS and OS, regardless of programmed death ligand-1.

Technical aspects of the use of cytopathological specimens for diagnosis and predictive testing in malignant epithelial neoplasms of the lung

Lung cancer is a leading cause of cancer mortality worldwide but recent years have seen a rapidly rising proportion of cases of advanced non-small cell carcinoma amenable to increasingly targeted therapy, initially based on the differential response to systemic treatment of tumours of squamous or glandular differentiation. In two-thirds of the cases, where patients present with advanced disease, both primary pathological diagnosis and biomarker testing is based on small biopsies and cytopathological specimens. The framework of this article is an overview of the technical aspect of each stage of the specimen pathway with emphasis on maximising potential for success when using small cytology samples. It brings together the current literature addressing pre-analytical and analytical aspects of specimen acquisition, performing rapid onsite evaluation, and undertaking diagnostic and predictive testing using immunocytochemistry and molecular platforms. The advantages and drawbacks of performing analysis on cell block and non-cell block specimen preparations is discussed.

Identification of Key Genes Related to CD8+ T-Cell Infiltration as Prognostic Biomarkers for Lung Adenocarcinoma

Background

CD8+ T cells are one of the central effector cells in the immune microenvironment. CD8+ T cells play a vital role in the development and progression of lung adenocarcinoma (LUAD). This study aimed to explore the key genes related to CD8+ T-cell infiltration in LUAD and to develop a novel prognosis model based on these genes.

Methods

With the use of the LUAD dataset from The Cancer Genome Atlas (TCGA), the differentially expressed genes (DEGs) were analyzed, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Combined with the CIBERSORT algorithm, the gene module in WGCNA, which was the most significantly correlated with CD8+ T cells, was selected for the subsequent analyses. Key genes were then identified by co-expression network analysis, protein–protein interactions network analysis, and least absolute shrinkage and selection operator (Lasso)-penalized Cox regression analysis. A risk assessment model was built based on these key genes and then validated by the dataset from the Gene Expression Omnibus (GEO) database and multiple fluorescence in situ hybridization experiments of a tissue microarray.

Results

Five key genes (MZT2A, ALG3, ATIC, GPI, and GAPDH) related to prognosis and CD8+ T-cell infiltration were identified, and a risk assessment model was established based on them. We found that the risk score could well predict the prognosis of LUAD, and the risk score was negatively related to CD8+ T-cell infiltration and correlated with the advanced tumor stage. The results of the GEO database and tissue microarray were consistent with those of TCGA. Furthermore, the risk score was higher significantly in tumor tissues than in adjacent lung tissues and was correlated with the advanced tumor stage.

Conclusions

This study may provide a novel risk assessment model for prognosis prediction and a new perspective to explore the mechanism of tumor immune microenvironment related to CD8+ T-cell infiltration in LUAD.

Current Status of Immune Checkpoint Inhibitor Immunotherapy for Lung Cancer

Immunotherapy is a major breakthrough in the treatment of cancer in recent years. Immune checkpoint inhibitors (ICIs) including programmed death-ligand 1 (PD-L1)/programmed death-1 (PD-1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) have been used for different histologic types of cancer including primary lung cancer that represents the most common and fatal cancer globally. Among ICI immunotherapy agents, atezolizumab, durvalumab, ipilimumab, nivolumab, and pembrolizumab are currently used as standard-of-care (SOC) treatment for metastatic or earlier stages of lung cancer. Major issues of ICI immunotherapy in lung cancer comprise the use of immune biomarkers prior to ICI therapy, selection of ICI agents, combination of ICIs/chemotherapy, combination of ICIs/radiotherapy, sequence of tyrosine kinase inhibitor (TKI) targeted therapy and ICI immunotherapy, sequence of chemotherapy and ICI immunotherapy, treatment duration of ICI regimen and ICI therapy for different histopathology, stage, PD-L1, and performance status. Based on the contemporary major clinical trials and authoritative guidelines, the objective of this review is to present an overview of the current status of ICI immunotherapy in lung cancer.

EGFR-Mutated Squamous Cell Lung Cancer and Its Association With Outcomes

Background

The therapeutic efficacy of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in advanced EGFR-mutant lung squamous cell carcinoma (SCC) patients remains uncertain. Furthermore, the factors underlying the responsiveness have not been fully investigated. We therefore investigated the link between genomic profiles and EGFR-TKI efficacy.

Material and Methods

We consecutively enrolled stage IV, EGFR-mutant, and EGFR-TKI–treated patients with SCC. Patients with EGFR wild-type lung SCC and EGFR-mutant lung adenocarcinoma were consecutively enrolled as controls, and next-generation sequencing (NGS) was performed.

Results

In total, 28 EGFR-mutant lung SCC, 41 EGFR-mutant lung adenocarcinoma, and 40 EGFR wild-type lung SCC patients were included. Among the patients with EGFR mutations, shorter progression-free survival (PFS) was observed in SCC compared to adenocarcinoma (4.6 vs. 11.0 months, P<0.001). Comparison of the genomic profiles revealed that EGFR-mutant SCC patients had similar mutation characteristics to EGFR-mutant adenocarcinoma patients, but differed from those with EGFR wild-type SCC. Further exploration of EGFR-mutant SCC revealed that mutations in CREBBP (P = 0.005), ZNF217 (P = 0.016), and the Wnt (P = 0.027) pathway were negatively associated with PFS. Mutations in GRM8 (P = 0.025) were associated with improved PFS.

Conclusions

EGFR-mutant lung SCC has a worse prognosis than EGFR-mutant adenocarcinoma. Mutations in other genes, such as CREBBP, ZNF217, GRM8, or Wnt that had implications on PFS raise the possibility of understanding mechanisms of resistance to EGFR-TKI in lung SCC, which will aid identification of potential beneficial subgroups of patients with EGFR-mutant SCCs receiving EGFR-TKIs.

Characterization of Circulating T Cell Receptor Repertoire Provides Information about Clinical Outcome after PD-1 Blockade in Advanced Non-Small Cell Lung Cancer Patients

Simple Summary

Immune checkpoint blockers (ICBs) have demonstrated durable anti-tumor responses in advanced non-small cell lung cancer (NSCLC). Despite progress in development of new predictive biomarkers, such as PD-L1 expression, TMB, or MSI, there is still an urge for a better selection of patients that will benefit from the blockade of PD-1/PD-L1 axis. In this study, peripheral blood T cell receptor beta chain (TCR-β) repertoire, at baseline (PRE) and first response (FR) assessment, was analyzed with high-throughput sequencing in a cohort of advanced NSCLC patients receiving first-line pembrolizumab. Our results suggest that measuring TCR-β features in peripheral blood may be a potential tool to assess patients’ immune response. Furthermore, the usage of the TRBV20-1 segment highly predicts host response and survival in anti-PD-1 treated NSCLC patients.

Abstract

Despite the success of immunotherapies in lung cancer, development of new biomarkers for patient selection is urgently needed. This study aims to explore minimally invasive approaches to characterize circulating T cell receptor beta chain (TCR-β) repertoire in a cohort of advanced non-small cell lung cancer (NSCLC) patients treated with first-line pembrolizumab. Peripheral blood samples were obtained at two time points: i) pretreatment (PRE) and ii) first response assessment (FR). Next-generation sequencing (NGS) was used to analyze the hypervariable complementary determining region 3 (CDR3) of TCR-β chain. Richness, evenness, convergence, and Jaccard similarity indexes plus variable (V) and joining (J)-gene usage were studied. Our results revealed that increased richness during treatment was associated with durable clinical benefit (DCB; p = 0.046), longer progression-free survival (PFS; p = 0.007) and overall survival (OS; p = 0.05). Patients with Jaccard similarity index ≥0.0605 between PRE and FR samples showed improved PFS (p = 0.021). Higher TRBV20-1 PRE usage was associated with DCB (p = 0.027). TRBV20-1 levels ≥9.14% in PRE and ≥9.02% in FR significantly increased PFS (p = 0.025 and p = 0.016) and OS (p = 0.035 and p = 0.018). Overall, analysis of circulating TCR-β repertoire may provide information about the immune response in anti-PD-1 treated NSCLC patients; in this scenario, it can also offer important information about the clinical outcome.

Non-Small Cell Lung Cancer Harboring Concurrent EGFR Genomic Alterations: A Systematic Review and Critical Appraisal of the Double Dilemma

The molecular pathways which promote lung cancer cell features have been broadly explored, leading to significant improvement in prognostic and diagnostic strategies. Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have dramatically altered the treatment approach for patients with metastatic non-small cell lung cancer (NSCLC). Latest investigations by using next-generation sequencing (NGS) have shown that other oncogenic driver mutations, believed mutually exclusive for decades, could coexist in EGFR-mutated NSCLC patients. However, the exact clinical and pathological role of concomitant genomic aberrations needs to be investigated. In this systematic review, we aimed to summarize the recent data on the oncogenic role of concurrent genomic alterations, by specifically evaluating the characteristics, the pathological significance, and their potential impact on the treatment approach.

What Is New in Biomarker Testing at Diagnosis of Advanced Non-Squamous Non-Small Cell Lung Carcinoma? Implications for Cytology and Liquid Biopsy

The discovery and clinical validation of biomarkers predictive of the response of non-squamous non-small-cell lung carcinomas (NS-NSCLC) to therapeutic strategies continue to provide new data. The evaluation of novel treatments is based on molecular analyses aimed at determining their efficacy. These tests are increasing in number, but the tissue specimens are smaller and smaller and/or can have few tumor cells. Indeed, in addition to tissue samples, complementary cytological and/or blood samples can also give access to these biomarkers. To date, it is recommended and necessary to look for the status of five genomic molecular biomarkers (EGFR, ALK, ROS1, BRAFV600, NTRK) and of a protein biomarker (PD-L1). However, the short- and more or less long-term emergence of new targeted treatments of genomic alterations on RET and MET, but also on others’ genomic alteration, notably on KRAS, HER2, NRG1, SMARCA4, and NUT, have made cellular and blood samples essential for molecular testing. The aim of this review is to present the interest in using cytological and/or liquid biopsies as complementary biological material, or as an alternative to tissue specimens, for detection at diagnosis of new predictive biomarkers of NS-NSCLC.

Analysis of the Gut Microbiota: An Emerging Source of Biomarkers for Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer

BACKGROUND

The human gut harbors around 10¹³-10¹⁴ microorganisms, collectively referred to as gut microbiota. Recent studies have found that the gut microbiota may have an impact on the interaction between immune regulation and anti-cancer immunotherapies.

METHODS

In order to characterize the diversity and composition of commensal microbiota and its relationship with response to immune checkpoint blockade (ICB), 16S ribosomal DNA (rDNA) sequencing was performed on 69 stool samples from advanced non-small cell lung cancer (NSCLC) patients prior to treatment with ICB.

RESULTS

The use of antibiotics and ICB-related skin toxicity were significantly associated with reduced gut microbiota diversity. However, antibiotics (ATB) usage was not related to low ICB efficacy. Phascolarctobacterium was enriched in patients with clinical benefit and correlated with prolonged progression-free survival, whereas Dialister was more represented in patients with progressive disease, and its higher relative abundance was associated with reduced progression-free survival and overall survival, with independent prognostic value in multivariate analysis.

CONCLUSIONS

Our results corroborate the relation between the baseline gut microbiota composition and ICB clinical outcomes in advanced NSCLC patients, and provide novel potential predictive and prognostic biomarkers for immunotherapy in NSCLC.

PD-L1 in Cytological Samples: A Review and a Practical Approach

With a growing number of predictive biomarkers needed to manage patients with non-small cell lung cancer (NSCLC), there has been a paradigm shift in care and handling of diagnostic samples. Among the various testing methods, immunohistochemistry (IHC) is the most cost- effective and widely available. Furthermore, over the past decade immunotherapy has emerged as one of the most promising cancer treatments. In this scenario IHC is the most used testing method available for PDL-1/PD1 immunotherapy. Several monoclonal antibodies targeting programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) pathways have been integrated into standard-of-care treatments of a wide range of cancer types, once provided evidence of PD-L1 expression in tumor cells by immunohistochemistry (IHC). Since currently available PD-L1 assays have been developed on formalin-fixed paraffin embedded (FFPE) histological specimens, a growing body of research is being dedicated to confirm the feasibility of applying PDL-1 assays also to cytological samples. Albeit promising results have been reported, several important issues still need to be addressed. Among these are the type of cytological samples, pre-analytical issues, cyto-histological correlation, and inter-observer agreement. This review briefly summarizes the knowledge of the role of cytopathology in the analysis of PD-L1 by immunocytochemistry (ICC) and future directions of cytopathology in the immunotherapy setting.

PD-L1 and beyond: Immuno-oncology in cytopathology

Over the past decade, immunotherapy has emerged as one of the most promising cancer treatments. Several monoclonal antibodies targeting the programmed death 1 (PD-1)/ programmed death ligand-1 (PD-L1) pathway have been integrated into standard-of-care treatments for a wide range of cancer types. Although all the available PD-L1 immunohistochemistry (IHC) assays have been developed on formalin-fixed histological specimens, a growing body of research has recently suggested the feasibility of PD-L1 testing on cytological samples. Although promising results have been reported, several important issues still need to be addressed. Among these are pre-analytical issues, cyto-hystological correlation, and inter-observer agreement. This review will briefly summarise the knowledge gaps and future directions of cytopathology in the immuno-oncology scenario.

Next generation sequencing in cytology

The application of next generation sequencing (NGS) technology to cytological samples has significantly modified molecular cytopathology practice. Cytological samples represent a valid source of high-quality DNA for NGS analysis, especially for predicting patients' response to targeted treatments and for refining the risk of malignancy in indeterminate cytological diagnoses. However, several pre-analytical factors may influence the reliability of NGS clinical analysis. Here, we briefly review the challenges of NGS in cytology practice, focusing on those pre-analytical factors that may negatively affect NGS success rates and routine diagnostic applications. Finally, we address the future directions of the field.

The Role of the Pathologist in the Next-Generation Era of Tumor Molecular Characterization

Current pathology practice is being shaped by the increasing complexity of modern medicine, in particular of precision oncology, and major technological advances. In the "next-generation technologies era", the pathologist has become the person responsible for the integration and interpretation of morphologic and molecular information and for the delivery of critical answers to diagnostic, prognostic and predictive queries, acquiring a prominent position in the molecular tumor boards.

Next Generation Sequencing in Cytopathology: Focus on Non-Small Cell Lung Cancer

Molecular cytopathology is a rapidly evolving field embracing both conventional microscopy and molecular pathology. Its growing popularity stems from the fact that in many types of advanced cancers, including non small cell lung cancer (NSCLC), cytological samples often constitute the only available specimens for morphomolecular analysis. Indeed, non formalin fixed and paraffin embedded (FFPE) cytological samples feature a higher quality of extracted nucleic acids than histological specimens. However, because of the growing complexity of molecular testing, several efforts should be made to validate the analytical performance of the wide array of currently available molecular technologies, including next generation sequencing (NGS). This technology has the terrific advantage of allowing simultaneous detection of scores of predictive biomarkers even in low-input DNA/RNA specimens. Here, we briefly review the role of the modern cytopathologist in the morphomolecular diagnosing of advanced stage NSCLC and the adoption of NGS in conventional cytopreparations (cell blocks, direct smears, and liquid-based cytology) and supernatants.