Most anaplastic lymphoma kinase (ALK)‐rearranged non‐small cell lung cancers (NSCLCs) show good clinical response to ALK inhibitors. However, some ALK‐rearranged NSCLC patients show various primary responses with unknown reasons. Previous studies focused on the clinical aspects of ALK fusions in small cohorts, or were conducted in vitro and/or in vivo to investigate the function of ALK. One of the suggested theories describes how echinoderm microtubule‐associated protein‐like 4 (EML4)–ALK variants play a role towards different sensitivities in ALK inhibitors. Until now, there has been no integrated comprehensive study that dissects ALK at the molecular level in a large scale. Here, we report the largest extensive molecular analysis of 158 ALK‐rearranged NSCLCs and have investigated these findings in a cell line construct experiment. We discovered that NSCLCs with EML4–ALK short forms (variant 3/others) had more advanced stage and frequent metastases than cases with the long forms (variant 1/others) (p = 0.057, p < 0.05). In vitro experiments revealed that EML4–ALK short forms show lower sensitivity to ALK inhibitors than do long forms. Clinical analysis also showed a trend for the short forms showing worse PFS. Interestingly, we found that breakpoints of ALK are evenly distributed mainly in intron 19 and almost all of them undergo a non‐homologous end‐joining repair to generate ALK fusions. We also discovered four novel somatic ALK mutations in NSCLC (T1151R, R1192P, A1280V, and L1535Q) that confer primary resistance; all of them showed strong resistance to ALK inhibitors, as G1202R does. Through targeted deep sequencing, we discovered three novel ALK fusion partners (GCC2, LMO7, and PHACTR1), and different ALK fusion partners showed different intracellular localization. With our findings that the EML4–ALK variants, new ALK somatic mutations, and novel ALK‐fusion partners may affect sensitivity to ALK inhibitors, we stress the importance of targeted therapy to take the ALK molecular profiling into consideration. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

For decades, research relating to modification of host immunity towards antitumor response activation has been ongoing, with the breakthrough discovery of immune-checkpoint blockers. Several biomarkers with potential predictive value have been reported in recent studies for these novel therapies. However, with the plethora of therapeutic options existing for a given cancer entity, modern oncology is now being confronted with multifactorial interpretation to devise “the best therapy” for the individual patient. Into the bargain come the multiverse guidelines for established and emerging diagnostic biomarkers, as well as the complex interplay between cancer cells and tumor microenvironment, provoking immense challenges in the therapy decision-making process. Through this review, we present various molecular diagnostic modalities and techniques, such as genomics, immunohistochemistry and quantitative image analysis, which have the potential of becoming powerful tools in the development of an optimal treatment regime when analogized with patient characteristics. We will summarize the underlying complexities of these methods and shed light upon the necessary considerations and requirements for data integration. It is our hope to provide compelling evidence to emphasize on the need for inclusion of integrative data analysis in modern cancer therapy, and thereupon paving a path towards precision medicine and better patient outcomes.

Purpose: Treatment with immune checkpoint inhibitors (ICI) in advanced melanoma can result in durable responses, yet an algorithm to decide which patients can safely discontinue ICI is still lacking. Experimental Design: We used a multimodal approach combining clinical data, artificial intelligence–based analysis of hematoxylin and eosin–stained whole-slide images of melanoma before ICI start, and gene expression signatures to identify biomarkers for relapse after discontinuing ICI in the absence of treatment progression. Results: Univariable Cox regression analysis identified the best overall response, mRNA expression of six genes, tumor cell density, and the lymphocyte-to-plasma cell ratio as factors predictive of relapse upon the cessation of the ICI. Multivariable Cox regression analysis showed that both TGFBR1 expression and the integral digital pathology parameter–based prognostic system were independently associated with relapse after ICI discontinuation. Training a multivariate adaptive regression spline model achieved the highest overall predictive accuracy of 84.6% for relapse after ICI discontinuation. Conclusions: The identified prognostic markers are fully explainable and easily implementable in routine practice, facilitating risk stratification upon the cessation of ICI therapy.

Cervical cancer remains a leading cause of cancer-related deaths in women worldwide, with limited treatment options for advanced stages and therapy-resistant cases. Despite advances in treatment, the variability in the patient response to standard therapies underscores the need for molecular biomarkers to guide personalized treatment strategies. This study aimed to explore the transcriptomic changes associated with the therapeutic response in locally advanced cervical cancer, focusing on 770 immune-related genes. We employed a digital multiplexed gene expression analysis, comparing gene expression profiles between matching pre- and post-treatment samples. The results revealed the significant upregulation of C7 and EGR2 in the post-treatment samples, suggesting that enhanced immune activity is a key factor in therapeutic success. Conversely, IL17RB, S100A7, and SAA1 were upregulated in the pre-treatment samples, potentially indicating resistance mechanisms. Pathway enrichment analysis highlighted that the immune response and apoptosis pathways are crucial to post-treatment changes. These findings suggest that C7, EGR2, and IL17RB may serve as biomarkers for predicting therapeutic outcomes and could inform the development of more effective, individualized treatment strategies for cervical cancer. This study provides new insights into the molecular mechanisms underlying treatment response and resistance.

Spontaneous pneumothorax (SP) in women of reproductive age with causes such as thoracic endometriosis syndrome (TES) presents a diagnostic and therapeutic challenge. A 33-year-old women was treated conservatively with chest tube insertion for a first occurrence of a right-sided pneumothorax in September 2015. In January 2016, a right-sided video-assisted thoracoscopic surgery (VATS) wedge resection and partial parietal pleurectomy was performed due to a recurrence. A right-sided VATS was again performed in December 2016 with multiple wedge resections and a total pleurectomy revealing a pulmonary Langerhans’ cell histiocytosis (PLCH) in the histological and immunohistochemical examinations. The patient was recommended an abstinence of smoking and further course was unremarkable until May 2019, when due to a recurrent pneumothorax, she received a talc pleurodesis via right-sided VATS. Due to yet another recurrence, she underwent a talc slurry pleurodesis over a right sided chest drain. In March 2020 due to recurrence, a right-sided VATS was performed and a blueish nodular lesion was resected from the diaphragm. The histological examination revealed an endometriosis with a diagnosis of TES. Since the patient did not exhibit a temporal relationship between her periods and the onset of pneumothorax symptoms, a final diagnosis of non-catamenial endometriosis-related pneumothorax was made. The patient is currently continuing smoking abstinence and is under hormone therapy. She has not presented with a recurrence. In clinical practice, it is important not to just relay on the information available to us, but to reevaluate the patient history to uncover new clues leading to a new diagnosis.