A systems pathology model for predicting overall survival in patients with refractory, advanced non-small-cell lung cancer treated with gefitinib

Editorial: 2021 European Society for Medical Oncology (ESMO) Recommendations on Laboratory Diagnostics for RET Gene Fusions and Mutations: A New Era in Targeted Therapy for RET-Altered Solid Tumors

During the past four decades, the identification of phenotypic changes in malignant tumor cells has been refined by the standardization of immunohistochemistry methods. Regulatory-approved companion diagnostics were initially developed for immunohistochemistry and to support early tumor tissue-based clinical trials. In the last decade, molecular profiling and gene sequencing data have identified specific molecular targets that have resulted in increasing drug development programs and regulatory approvals. As an example, RET-altered cancers include RET gene mutations and RET gene fusions. In January 2021, the European Society for Medical Oncology (ESMO) published new guidelines for routine clinical laboratory detection of targetable RET gene rearrangements and mutations. FDA approval has now been given for selpercatinib for RET fusion-positive NSCLC and papillary thyroid cancer, and RET mutation-positive thyroid cancer. This Editorial aims to present a brief overview of the evolution of personalized medicine in oncology and how the 2021 ESMO guidelines have anticipated the need to detect targetable RET-altered tumors using technology currently available in accredited clinical diagnostic laboratories.

A personalized platform identifies trametinib plus zoledronate for a patient with KRAS-mutant metastatic colorectal cancer

Colorectal cancer remains a leading source of cancer mortality worldwide. Initial response is often followed by emergent resistance that is poorly responsive to targeted therapies, reflecting currently undruggable cancer drivers such as KRAS and overall genomic complexity. Here, we report a novel approach to developing a personalized therapy for a patient with treatment-resistant metastatic KRAS-mutant colorectal cancer. An extensive genomic analysis of the tumor's genomic landscape identified nine key drivers. A transgenic model that altered orthologs of these nine genes in the Drosophila hindgut was developed; a robotics-based screen using this platform identified trametinib plus zoledronate as a candidate treatment combination. Treating the patient led to a significant response: Target and nontarget lesions displayed a strong partial response and remained stable for 11 months. By addressing a disease's genomic complexity, this personalized approach may provide an alternative treatment option for recalcitrant disease such as KRAS-mutant colorectal cancer.

Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

Implementation of a Precision Pathology Program Focused on Oncology-Based Prognostic and Predictive Outcomes

Personalized or precision medicine as a diagnostic and therapeutic paradigm was introduced some 10-15 years ago, with the advent of biomarker discovery as a mechanism for identifying prognostic and predictive attributes associated with treatment indication and outcome. While the concept is not new, the successful development and implementation of novel 'companion diagnostics', especially in oncology, continues to represent a significant challenge and is currently at the forefront of smart trial design and therapeutic choice. The ability to determine patient selection for a specific therapy has broad implications including better chances for a positive outcome, limited exposure to potentially toxic drugs and improved health economics. Importantly, a significant step in this paradigm is the role of predictive pathology or the accurate assessment of morphology at the microscopic level. In breast cancer, this has been most useful where histologic attributes such as the classification of tubular and cribriform carcinoma dictates surgery while neoadjuvant studies suggest that patients with lobular carcinoma are not likely to benefit from chemotherapy. The next level of 'personalized pathology' at the tissue-cellular level is the use of 'protein biomarker panels' to classify the disease process and ultimately drive tumor characterization and treatment. The following review article will focus on the evolution of predictive pathology from a subjective, 'opinion-based' approach to a quantitative science. In addition, we will discuss the individual components of the precise pathology platform including advanced image analysis, biomarker quantitation with mathematical modeling and the integration with fluid-based (i.e. blood, urine) analytics as drivers of next generation precise patient phenotyping.

Screening for patients with non-small cell lung cancer who could survive long term chemotherapy

BACKGROUND

Lung cancer was one of the most common cancers in both men and women all over the world. In this study, we aimed to clarify who could survive after long term chemotherapy in patients with advanced non-small cell lung cancer (NSCLC).

METHODS

We enrolled 186 patients with stage IV NSCLC after long term chemotherapy from Jun 2006 to Nov 2014 diagnosed in Jiangsu Cancer Hospital. Multiple variables like age, gender, smoking, histology of adenocarcinoma and squamous-cell cancer, number of metastatic sites, metastatic sites (e.g. lung, brain, bone, liver and pleura), hemoglobin, lymphocyte rate (LYR), Change of LYR during multiple therapies, hypertension, diabetes, chronic bronchitis, treatments (e.g.radiotherapy and targeted therapy) were selected. For consideration of factors influencing survival and response for patients with advanced NSCLC, logistic regression analysis and Cox regression analysis were used in an attempt to develop a screening module for patients with elevated survival after long term chemotherapy become possible.

RESULTS

Of the total of 186 patients enrolled, 69 survived less than 1 year (short-term group), 45 one to two years, and 72 longer than 3 years (long-term group). For logistic regression analysis, the short-term group was taken as control group and the long-term group as the case group. We found that age, histology of adenocarcinoma, metastatic site (e.g. lung and liver), treatments (e.g. targeted therapy and radiotherapy), LYR, a decreasing tendency of LYR and chronic bronchitis were individually associated with overall survival by Cox regression analysis. A multivariable Cox regression model showed that metastatic site (e.g. lung and liver), histology of adenocarcinoma, treatments (e.g. targeted therapy and radiotherapy) and chronic bronchitis were associated with overall survival. Thus metastatic site (e.g. lung and liver) and chronic bronchitis may be important risk factors for patients with advanced NSCLC. Gender, metastatic site (e.g. lung and liver), LYR and the decreasing tendency of LYR were significantly associated with long-term survival in the individual-variable logistic regression model (P<0.05). On multivariate logistic regression analysis, gender, metastatic site (e.g. lung and liver) and the decreasing tendency of LYR associated with long-term survival.

CONCLUSIONS

In conclusion, female patients with stage IV adenocarcinoma of NSCLC who had decreasing tendency of LYR during the course therapy and had accepted multiple therapies e.g. more than third-line chemotherapy, radiotherapy and/or targeted therapy might be expected to live longer.

Modeling the overall survival of patients with advanced-stage non-small cell lung cancer using data of routine laboratory tests

Cancer patients undergo routine clinical monitoring with an array of blood tests that may carry long-term prognostic information. We aimed to develop a new prognostic model predicting survival for patients with advanced non-small cell lung cancer (NSCLC), based on laboratory tests commonly performed in clinical practice. A cohort of 1,161 stage IIIB or IV NSCLC patients was divided into training (n = 773) and testing (n = 388) cohorts. We analyzed the associations of 32 commonly tested laboratory variables with patient survival in the training cohort. We developed a model based on those significant laboratory variables, together with important clinical variables. The model was then evaluated in the testing cohort. Five variables, including albumin, total protein, alkaline phosphatase, blood urea nitrogen and international normalized ratio, were significantly associated with patient survival after stepwise selection. A model incorporating these variables classified patients into low-, medium- and high-risk groups with median survival of 16.9, 7.2 and 2.1 months, respectively (p < 0.0001). Compared with low-risk group, patients in the medium- and high-risk groups had a significantly higher risk of death at 1 year, with hazard ratio (HR) of 1.95 (95% CI 1.62-2.36) and 5.22 (4.30-6.34), respectively. These results were validated in the testing cohort. Overall, we developed a prognostic model relying entirely on readily available variables, with similar predictive power to those which depend on more specialized and expensive molecular assays. Further study is necessary to validate and further refine this model, and compare its performance to models based on more specialized and expensive testing.

Multispectral Imaging

The field of anatomic pathology has changed significantly over the last decades and, as a result of the technological developments in molecular pathology and genetics, has had increasing pressures put on it to become quantitative and to provide more information about protein expression on a cellular level in tissue sections. Multispectral imaging (MSI) has a long history as an advanced imaging modality and has been used for over a decade now in pathology to improve quantitative accuracy, enable the analysis of multicolor immunohistochemistry, and drastically reduce the impact of contrast-robbing tissue autofluorescence common in formalin-fixed, paraffin-embedded tissues. When combined with advanced software for the automated segmentation of different tissue morphologies (eg, tumor vs stroma) and cellular and subcellular segmentation, MSI can enable the per-cell quantitation of many markers simultaneously. This article covers the role that MSI has played in anatomic pathology in the analysis of formalin-fixed, paraffin-embedded tissue sections, discusses the technological aspects of why MSI has been adopted, and provides a review of the literature of the application of MSI in anatomic pathology.

DNA-Mutation Inventory to Refine and Enhance Cancer Treatment (DIRECT): a catalog of clinically relevant cancer mutations to enable genome-directed anticancer therapy

PURPOSE

Tumor gene mutation status is becoming increasingly important in the treatment of patients with cancer. A comprehensive catalog of tumor gene-response outcomes from individual patients is needed, especially for actionable mutations and rare variants. We created a proof-of-principle database [DNA-mutation Inventory to Refine and Enhance Cancer Treatment (DIRECT)], starting with lung cancer-associated EGF receptor (EGFR) mutations, to provide a resource for clinicians to prioritize treatment decisions based on a patient's tumor mutations at the point of care.

METHODS

A systematic search of literature published between June 2005 and May 2011 was conducted through PubMed to identify patient-level, mutation-drug response in patients with non-small cell lung cancer (NSCLC) with EGFR mutant tumors. Minimum inclusion criteria included patient's EGFR mutation, corresponding treatment, and an associated radiographic outcome.

RESULTS

A total of 1,021 patients with 1,070 separate EGFR tyrosine kinase inhibitor therapy responses from 116 different publications were included. About 188 unique EGFR mutations occurring in 207 different combinations were identified: 149 different mutation combinations were associated with disease control and 42 were associated with disease progression. Four secondary mutations, in 16 different combinations, were associated with acquired resistance.

CONCLUSIONS

As tumor sequencing becomes more common in oncology, this comprehensive electronic catalog can enable genome-directed anticancer therapy. DIRECT will eventually encompass all tumor mutations associated with clinical outcomes on targeted therapies. Users can make specific queries at http://www.mycancergenome.org/about/direct to obtain clinically relevant data associated with various mutations.

Why is it crucial to reintegrate pathology into cancer research?

The integration of pathology with molecular biology is vital if we are to enhance the translational value of cancer research. Pathology represents a bridge between medicine and basic biology, it remains the gold standard for cancer diagnosis, and it plays an important role in discovery studies. In the past, pathology and cancer research were closely associated; however, the molecular biology revolution has shifted the focus of investigators toward the molecular alterations of tumors. The reductionist approach taken in molecular studies is producing great insight into the inner workings of neoplasia, but it can also minimize the importance of histopathology and of understanding the disease as a whole. In turn, pathologists can underestimate the role of molecular studies in developing new ancillary techniques for clinical diagnosis. A multidisciplinary approach that integrates pathology and molecular biology within a translational research system is needed. This process will require overcoming cultural barriers and can be achieved through education, a more effective incorporation of pathology into biological research, and conversely an integration of biological research into the pathology laboratory.

Gefitinib in combination with irradiation with or without cisplatin in patients with inoperable stage III non-small cell lung cancer: a phase I trial

PURPOSE

To establish the feasibility and tolerability of gefitinib (ZD1839, Iressa) with radiation (RT) or concurrent chemoradiation (CRT) with cisplatin (CDDP) in patients with advanced non-small cell lung cancer (NSCLC).

PATIENTS AND METHODS

In this multicenter Phase I study, 5 patients with unresectable NSCLC received 250 mg gefitinib daily starting 1 week before RT at a dose of 63 Gy (Step 1). After a first safety analysis, 9 patients were treated daily with 250 mg gefitinib plus CRT in the form of RT and weekly CDDP 35 mg/m(2) (Step 2). Gefitinib was maintained for up to 2 years until disease progression or toxicity.

RESULTS

Fourteen patients were assessed in the two steps. In Step 1 (five patients were administered only gefitinib and RT), no lung toxicities were seen, and there was no dose-limiting toxicity (DLT). Adverse events were skin and subcutaneous tissue reactions, limited to Grade 1-2. In Step 2, two of nine patients (22.2%) had DLT. One patient suffered from dyspnea and dehydration associated with neutropenic pneumonia, and another showed elevated liver enzymes. In both steps combined, 5 of 14 patients (35.7%) experienced one or more treatment interruptions.

CONCLUSIONS

Gefitinib (250 mg daily) in combination with RT and CDDP in patients with Stage III NSCLC is feasible, but CDDP likely enhances toxicity. The impact of gefitinib on survival and disease control as a first-line treatment in combination with RT remains to be determined.