Successful Treatment of Patients with Refractory High-Grade Serous Ovarian Cancer with GOPC-ROS1 Fusion Using Crizotinib: A Case Report

Overcoming Chemoresistance in Cancer: The Promise of Crizotinib

Chemoresistance is a major obstacle in cancer treatment, often leading to disease progression and poor outcomes. It arises through various mechanisms such as genetic mutations, drug efflux pumps, enhanced DNA repair, and changes in the tumor microenvironment. These processes allow cancer cells to survive despite chemotherapy, underscoring the need for new strategies to overcome resistance and improve treatment efficacy. Crizotinib, a first-generation multi-target kinase inhibitor, is approved by the FDA for the treatment of ALK-positive or ROS1-positive non-small cell lung cancer (NSCLC), refractory inflammatory (ALK)-positive myofibroblastic tumors (IMTs) and relapsed/refractory ALK-positive anaplastic large cell lymphoma (ALCL). Crizotinib exists in two enantiomeric forms: (R)-crizotinib and its mirror image, (S)-crizotinib. It is assumed that the R-isomer is responsible for the carrying out various processes reviewed here The S-isomer, on the other hand, shows a strong inhibition of MTH1, an enzyme important for DNA repair mechanisms. Studies have shown that crizotinib is an effective multi-kinase inhibitor targeting various kinases such as c-Met, native/T315I Bcr/Abl, and JAK2. Its mechanism of action involves the competitive inhibition of ATP binding and allosteric inhibition, particularly at Bcr/Abl. Crizotinib showed synergistic effects when combined with the poly ADP ribose polymerase inhibitor (PARP), especially in ovarian cancer harboring BRCA gene mutations. In addition, crizotinib targets a critical vulnerability in many p53-mutated cancers. Unlike its wild-type counterpart, the p53 mutant promotes cancer cell survival. Crizotinib can cause the degradation of the p53 mutant, sensitizing these cancer cells to DNA-damaging substances and triggering apoptosis. Interestingly, other reports demonstrated that crizotinib exhibits anti-bacterial activity, targeting Gram-positive bacteria. Also, it is active against drug-resistant strains. In summary, crizotinib exerts anti-tumor effects through several mechanisms, including the inhibition of kinases and the restoration of drug sensitivity. The potential of crizotinib in combination therapies is emphasized, particularly in cancers with a high prevalence of the p53 mutant, such as triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSOC).

Ovarian cancer ascites confers platinum chemoresistance to ovarian cancer cells

Ovarian cancer (OC), the second most common form of gynecologic malignancy, has a poor prognosis and is often discovered in the late stages. Platinum-based chemotherapy is the first line of therapy. Nevertheless, treatment OC has proven challenging due to toxicity and the development of acquired resistance to therapy. Tumor microenvironment (TME) has been associated with platinum chemoresistance. Malignant ascites has been used as OC tumor microenvironment and its ability to induce platinum chemoresistance has been investigated. Our results suggest that exposure to OC ascites induces platinum chemoresistance in 11 of 13 cases (85 %) on OC cells. In contrast, 75 % of cirrhotic ascites (3 of 4) failed to confer platinum chemoresistance to OC cells. Cytokine array analysis revealed that IL -6 and to a lesser extent HGF were enriched in OC ascites, whereas IL -22 was enriched in cirrhotic ascites. Pharmaceutical inhibitors targeting the IL -6/ JAK pathway were mildly effective in overcoming platinum chemoresistance induced by malignant ascites. In contrast, crizotinib, an HGF/c- MET inhibitor, and 2-hydroxyestradiol (2HE2) were effective in restoring platinum chemosensitivity to OC. Our results demonstrate the importance of OC ascites in supporting platinum chemoresistance and the potential of combination therapy to restore chemosensitivity of OC cells.

Agnostic Administration of Targeted Anticancer Drugs: Looking for a Balance between Hype and Caution

Many tumors have well-defined vulnerabilities, thus potentially allowing highly specific and effective treatment. There is a spectrum of actionable genetic alterations which are shared across various tumor types and, therefore, can be targeted by a given drug irrespective of tumor histology. Several agnostic drug-target matches have already been approved for clinical use, e.g., immune therapy for tumors with microsatellite instability (MSI) and/or high tumor mutation burden (TMB), NTRK1-3 and RET inhibitors for cancers carrying rearrangements in these kinases, and dabrafenib plus trametinib for BRAF V600E mutated malignancies. Multiple lines of evidence suggest that this histology-independent approach is also reasonable for tumors carrying ALK and ROS1 translocations, biallelic BRCA1/2 inactivation and/or homologous recombination deficiency (HRD), strong HER2 amplification/overexpression coupled with the absence of other MAPK pathway-activating mutations, etc. On the other hand, some well-known targets are not agnostic: for example, PD-L1 expression is predictive for the efficacy of PD-L1/PD1 inhibitors only in some but not all cancer types. Unfortunately, the individual probability of finding a druggable target in a given tumor is relatively low, even with the use of comprehensive next-generation sequencing (NGS) assays. Nevertheless, the rapidly growing utilization of NGS will significantly increase the number of patients with highly unusual or exceptionally rare tumor-target combinations. Clinical trials may provide only a framework for treatment attitudes, while the decisions for individual patients usually require case-by-case consideration of the probability of deriving benefit from agnostic versus standard therapy, drug availability, associated costs, and other circumstances. The existing format of data dissemination may not be optimal for agnostic cancer medicine, as conventional scientific journals are understandably biased towards the publication of positive findings and usually discourage the submission of case reports. Despite all the limitations and concerns, histology-independent drug-target matching is certainly feasible and, therefore, will be increasingly utilized in the future.

Current treatment and novel insights regarding ROS1-targeted therapy in malignant tumors

BACKGROUND

The proto-oncogene ROS1 encodes an intrinsic type I membrane protein of the tyrosine kinase/insulin receptor family. ROS1 facilitates the progression of various malignancies via self-mutations or rearrangements. Studies on ROS1-directed tyrosine kinase inhibitors have been conducted, and some have been approved by the FDA for clinical use. However, the adverse effects and mechanisms of resistance associated with ROS1 inhibitors remain unknown. In addition, next-generation ROS1 inhibitors, which have the advantage of treating central nervous system metastases and alleviating endogenous drug resistance, are still in the clinical trial stage.

METHOD

In this study, we searched relevant articles reporting the mechanism and clinical application of ROS1 in recent years; systematically reviewed the biological mechanisms, diagnostic methods, and research progress on ROS1 inhibitors; and provided perspectives for the future of ROS1-targeted therapy.

RESULTS

ROS1 is most expressed in malignant tumours. Only a few ROS1 kinase inhibitors are currently approved for use in NSCLC, the efficacy of other TKIs for NSCLC and other malignancies has not been ascertained. There is no effective standard treatment for adverse events or resistance to ROS1-targeted therapy. Next-generation TKIs appear capable of overcoming resistance and delaying central nervous system metastasis, but with a greater incidence of adverse effects.

CONCLUSIONS

Further research on next-generation TKIs regarding the localization of ROS1 and its fusion partners, binding sites for targeted drugs, and coadministration with other drugs is required. The correlation between TKIs and chemotherapy or immunotherapy in clinical practice requires further study.

Metabolic-Related Gene Prognostic Index for Predicting Prognosis, Immunotherapy Response, and Candidate Drugs in Ovarian Cancer

Ovarian cancer (OC) is a highly heterogeneous disease, with patients at different tumor staging having different survival times. Metabolic reprogramming is one of the key hallmarks of cancer; however, the significance of metabolism-related genes in the prognosis and therapy outcomes of OC is unclear. In this study, we used weighted gene coexpression network analysis and differential expression analysis to screen for metabolism-related genes associated with tumor staging. We constructed the metabolism-related gene prognostic index (MRGPI), which demonstrated a stable prognostic value across multiple clinical trial end points and multiple validation cohorts. The MRGPI population had its distinct molecular features, mutational characteristics, and immune phenotypes. In addition, we investigated the response to immunotherapy in MRGPI subgroups and found that patients with low MRGPI were prone to benefit from anti-PD-1 checkpoint blockade therapy and exhibited a delayed treatment effect. Meanwhile, we identified four candidate therapeutic drugs (ABT-737, crizotinib, panobinostat, and regorafenib) for patients with high MRGPI, and we evaluated the pharmacokinetics and safety of the candidate drugs. In summary, the MRGPI was a robust clinical feature that could predict patient prognosis, immunotherapy response, and candidate drugs, facilitating clinical decision making and therapeutic strategy of OC.

Integrated analysis of ovarian cancer patients from prospective transcription factor activity reveals subtypes of prognostic significance

Transcription factors are protein molecules that act as regulators of gene expression. Aberrant protein activity of transcription factors can have a significant impact on tumor progression and metastasis in tumor patients. In this study, 868 immune-related transcription factors were identified from the transcription factor activity profile of 1823 ovarian cancer patients. The prognosis-related transcription factors were identified through univariate Cox analysis and random survival tree analysis, and two distinct clustering subtypes were subsequently derived based on these transcription factors. We assessed the clinical significance and genomics landscape of the two clustering subtypes and found statistically significant differences in prognosis, response to immunotherapy, and chemotherapy among ovarian cancer patients with different subtypes. Multi-scale Embedded Gene Co-expression Network Analysis was used to identify differential gene modules between the two clustering subtypes, which allowed us to conduct further analysis of biological pathways that exhibited significant differences between them. Finally, a ceRNA network was constructed to analyze lncRNA-miRNA-mRNA regulatory pairs with differential expression levels between two clustering subtypes. We expected that our study may provide some useful references for stratifying and treating patients with ovarian cancer.

Interstitial Deletions Generating Fusion Genes

A fusion gene is the physical juxtaposition of two different genes resulting in a structure consisting of the head of one gene and the tail of the other. Gene fusion is often a primary neoplasia-inducing event in leukemias, lymphomas, solid malignancies as well as benign tumors. Knowledge about fusion genes is crucial not only for our understanding of tumorigenesis, but also for the diagnosis, prognostication, and treatment of cancer. Balanced chromosomal rearrangements, in particular translocations and inversions, are the most frequent genetic events leading to the generation of fusion genes. In the present review, we summarize the existing knowledge on chromosome deletions as a mechanism for fusion gene formation. Such deletions are mostly submicroscopic and, hence, not detected by cytogenetic analyses but by array comparative genome hybridization (aCGH) and/or high throughput sequencing (HTS). They are found across the genome in a variety of neoplasias. As tumors are increasingly analyzed using aCGH and HTS, it is likely that more interstitial deletions giving rise to fusion genes will be found, significantly impacting our understanding and treatment of cancer.