Characterization of KRAS Mutational Regression in Oligometastatic Patients

Clinical and genetic drivers of oligo-metastatic disease in colon cancer

BACKGROUND

Oligo-metastatic disease (OMD) in colon cancer patients exhibits distinct clinical behavior compared to poly-metastatic disease (PMD), with a more responsive and indolent course. This study aims to identify clinical and biological factors uniquely associated with oligo-metastatic behavior.

METHODS

Metastatic colon cancer patients from an academic center underwent genetic characterization. OMD was defined as ≤3 lesions per organ, each with a total diameter <70 mm and none exceeding 25 mm. Tumor DNA sequencing by NGS utilized the TruSight Oncology 500 kit. Overall survival (OS) was determined from metastasis diagnosis until death using Kaplan-Meier analysis. Multivariate Cox regression examined prognostic links between clinicopathological and genetic factors. Associations with metastatic patterns were evaluated using Chi-square.

RESULTS

The analysis involved 104 patients (44 with OMD, 60 with PMD). OMD was more prevalent in males (P = 0.0299) and with single organ involvement (P = 0.0226). Multivariate analysis adjusted for age (>70 vs. <70 years), gender (male vs. female), tumor side (right vs. left), metastatic involvement (more than one site vs. one site), response to first-line therapy (disease control vs. no disease control), and RAS/BRAF variants (wild-type vs. mutated) identified OMD vs. PMD as the strongest independent predictor of survival (HR: 0.14; 95 % CI: 0.06-0.33; P<0.0001). OMD patients exhibited distinct molecular characteristics, including lower frequencies of BRAF p.V600E (P=0.0315) and KRAS mutations (P=0.0456), as well as a higher frequency of high tumor mutational burden (P=0.0127). Additionally, by integrating data from public datasets and our case study, we hypothesize that some gene alterations (i.e.: BRAF, SMAD4, RAF1, and mTOR) may prevent OMD occurrence.

CONCLUSION

OMD, characterized by male predominance, single-site involvement, and distinct molecular features in colon cancer, suggests the need for tailored management strategies.

The roles of KRAS in cancer metabolism, tumor microenvironment and clinical therapy

KRAS is one of the most mutated genes, driving alternations in metabolic pathways that include enhanced nutrient uptaking, increased glycolysis, elevated glutaminolysis, and heightened synthesis of fatty acids and nucleotides. However, the beyond mechanisms of KRAS-modulated cancer metabolisms remain incompletely understood. In this review, we aim to summarize current knowledge on KRAS-related metabolic alterations in cancer cells and explore the prevalence and significance of KRAS mutation in shaping the tumor microenvironment and influencing epigenetic modification via various molecular activities. Given that cancer cells rely on these metabolic changes to sustain cell growth and survival, targeting these processes may represent a promising therapeutic strategy for KRAS-driven cancers.

Repeat Next-Generation Sequencing (15-Gene Panel) in Unifocal, Synchronous, and Metachronous Non-Small-Cell Lung Cancer-A Single-Center Experience

In advanced non-squamous non-small-cell lung cancer (NSCLC), routine testing with next-generation sequencing (NGS) is recommended to identify actionable genomic alterations (AGAs). The therapeutic implications of repeated NGS testing on synchronous and metachronous tumors are unclear. Between February 2017 and October 2020, NSCLC samples from a single institution were reflex-tested using a targeted 15-gene NGS panel (TruSight Tumor 15, Illumina). Thirty-eight patients were identified with multiple NGS results from 82 samples: 11% were from single unifocal, 51% were from synchronous, and 38% were from metachronous tumors. Changes in EGFR, KRAS, PI3KCA, and TP53 variants were found in 22 patients' samples (58%). No changes were seen with longitudinal testing of multiple samples from single unifocal tumors, while changes were observed in 60% of synchronous and 71% of metachronous tumors. Of these, 26% of patients had AGA differences between samples. Acknowledging the limited sample size, a significant difference in overall survival was observed between synchronous separate primaries and metastasis. Repeat NGS testing of synchronous and metachronous NSCLC tumors may identify differing variants in >50% of patients. These changes may reflect separate primary lung carcinomas, tumor heterogeneity among intrapulmonary metastases, and clonal evolution. NGS testing of multiple tumors may enhance the identification of therapeutic targets for treatment decisions.

Optimizing Treatment Strategy for Oligometastases/Oligo-Recurrence of Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer, and nearly half of CRC patients experience metastases. Oligometastatic CRC represents a distinct clinical state characterized by limited metastatic involvement, demonstrating a less aggressive nature and potentially improved survival with multidisciplinary treatment. However, the varied clinical scenarios giving rise to oligometastases necessitate a precise definition, considering primary tumor status and oncological factors, to optimize treatment strategies. This review delineates the concepts of oligometastatic CRC, encompassing oligo-recurrence, where the primary tumor is under control, resulting in a more favorable prognosis. A comprehensive examination of multidisciplinary treatment with local treatments and systemic therapy is provided. The overarching objective in managing oligometastatic CRC is the complete eradication of metastases, offering prospects of a cure. Essential to this management approach are local treatments, with surgical resection serving as the standard of care. Percutaneous ablation and stereotactic body radiotherapy present less invasive alternatives for lesions unsuitable for surgery, demonstrating efficacy in select cases. Perioperative systemic therapy, aiming to control micrometastatic disease and enhance local treatment effectiveness, has shown improvements in progression-free survival through clinical trials. However, the extension of overall survival remains variable. The review emphasizes the need for further prospective trials to establish a cohesive definition and an optimized treatment strategy for oligometastatic CRC.

Oligo-Metastatic Disease in Oncology: Exploring the Limits and the Potential of Genetic Assessment

Oligo-metastatic disease (OMD) in the field of oncology denotes a distinct subset of metastatic tumors characterized by less aggressive biological behavior and extended survival times in comparison to their widely metastatic counterparts. While there is a general consensus regarding the existence of OMD, there remains a lack of widely accepted criteria for its a priori identification at the time of presentation. This review delves into the concept of OMD, placing a particular emphasis on the significance of understanding the limitations and potential of genetic assessments. It explores how these aspects are crucial in advancing our comprehension of this phenomenon. In a rapidly advancing era of precision medicine, understanding the intricacies of OMD opens up exciting possibilities for tailored treatment approaches. By elucidating the genetic underpinnings and dynamic nature of this condition, we stand to improve patient outcomes and potentially shift the paradigm of metastatic cancer management.

Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

OBJECTIVE

The aim of this study was the evaluation radiomics analysis efficacy performed using computed tomography (CT) and magnetic resonance imaging in the prediction of colorectal liver metastases patterns linked to patient prognosis: tumor growth front; grade; tumor budding; mucinous type. Moreover, the prediction of liver recurrence was also evaluated.

METHODS

The retrospective study included an internal and validation dataset; the first was composed by 119 liver metastases from 49 patients while the second consisted to 28 patients with single lesion. Radiomic features were extracted using PyRadiomics. Univariate and multivariate approaches including machine learning algorithms were employed.

RESULTS

The best predictor to identify tumor growth was the Wavelet_HLH_glcm_MaximumProbability with an accuracy of 84% and to detect recurrence the best predictor was wavelet_HLH_ngtdm_Complexity with an accuracy of 90%, both extracted by T1-weigthed arterial phase sequence. The best predictor to detect tumor budding was the wavelet_LLH_glcm_Imc1 with an accuracy of 88% and to identify mucinous type was wavelet_LLH_glcm_JointEntropy with an accuracy of 92%, both calculated on T2-weigthed sequence. An increase statistically significant of accuracy (90%) was obtained using a linear weighted combination of 15 predictors extracted by T2-weigthed images to detect tumor front growth. An increase statistically significant of accuracy at 93% was obtained using a linear weighted combination of 11 predictors by the T1-weigthed arterial phase sequence to classify tumor budding. An increase statistically significant of accuracy at 97% was obtained using a linear weighted combination of 16 predictors extracted on CT to detect recurrence. An increase statistically significant of accuracy was obtained in the tumor budding identification considering a K-nearest neighbors and the 11 significant features extracted T1-weigthed arterial phase sequence.

CONCLUSIONS

The results confirmed the Radiomics capacity to recognize clinical and histopathological prognostic features that should influence the choice of treatments in colorectal liver metastases patients to obtain a more personalized therapy.

Oligo-metastatic neoPlasms from the gastro-intestinal tract: iDentIfiCaTIon of cliNical and molecular drivers: the PREDICTION study

BACKGROUND

Metastatic disease in tumors originating from the gastrointestinal tract can exhibit varying degrees of tumor burden at presentation. Some patients follow a less aggressive disease course, characterized by a limited number of metastatic sites, referred to as "oligo-metastatic disease" (OMD). The precise biological characteristics that define the oligometastatic behavior remain uncertain. In this study, we present a protocol designed to prospectively identify OMD, with the aim of proposing novel therapeutic approaches and monitoring strategies.

METHODS

The PREDICTION study is a monocentric, prospective, observational investigation. Enrolled patients will receive standard treatment, while translational activities will involve analysis of the tumor microenvironment and genomic profiling using immunohistochemistry and next-generation sequencing, respectively. The first primary objective (descriptive) is to determine the prevalence of biological characteristics in OMD derived from gastrointestinal tract neoplasms, including high genetic concordance between primary tumors and metastases, a significant infiltration of T lymphocytes, and the absence of clonal evolution favoring specific driver genes (KRAS and PIK3CA). The second co-primary objective (analytic) is to identify a prognostic score for true OMD, with a primary focus on metastatic colorectal cancer. The score will comprise genetic concordance (> 80%), high T-lymphocyte infiltration, and the absence of clonal evolution favoring driver genes. It is hypothesized that patients with true OMD (score 3+) will have a lower rate of progression/recurrence within one year (20%) compared to those with false OMD (80%). The endpoint of the co-primary objective is the rate of recurrence/progression at one year. Considering a reasonable probability (60%) of the three factors occurring simultaneously in true OMD (score 3+), using a significance level of α = 0.05 and a test power of 90%, the study requires a minimum enrollment of 32 patients.

DISCUSSION

Few studies have explored the precise genetic and biological features of OMD thus far. In clinical settings, the diagnosis of OMD is typically made retrospectively, as some patients who undergo intensive treatment for oligometastases develop polymetastatic diseases within a year, while others do not experience disease progression (true OMD). In the coming years, the identification of true OMD will allow us to employ more personalized and comprehensive strategies in cancer treatment.

TRIAL REGISTRATION

ClinicalTrials.gov ID NCT05806151.

Oligo-Metastatic Cancers: Putative Biomarkers, Emerging Challenges and New Perspectives

Some cancer patients display a less aggressive form of metastatic disease, characterized by a low tumor burden and involving a smaller number of sites, which is referred to as "oligometastatic disease" (OMD). This review discusses new biomarkers, as well as methodological challenges and perspectives characterizing OMD. Recent studies have revealed that specific microRNA profiles, chromosome patterns, driver gene mutations (ERBB2, PBRM1, SETD2, KRAS, PIK3CA, SMAD4), polymorphisms (TCF7L2), and levels of immune cell infiltration into metastases, depending on the tumor type, are associated with an oligometastatic behavior. This suggests that OMD could be a distinct disease with specific biological and molecular characteristics. Therefore, the heterogeneity of initial tumor burden and inclusion of OMD patients in clinical trials pose a crucial methodological question that requires responses in the near future. Additionally, a solid understanding of the molecular and biological features of OMD will be necessary to support and complete the clinical staging systems, enabling a better distinction of metastatic behavior and tailored treatments.

Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.

Radiation Recall Pneumonitis: The Open Challenge in Differential Diagnosis of Pneumonia Induced by Oncological Treatments

The treatment of primary and secondary lung neoplasms now sees the fundamental role of radiotherapy, associated with surgery and systemic therapies. The improvement in survival outcomes has also increased attention to the quality of life, treatment compliance and the management of side effects. The role of imaging is not only limited to recognizing the efficacy of treatment but also to identifying, as soon as possible, the uncommon effects, especially when more treatments, such as chemotherapy, immunotherapy and radiotherapy, are associated. Radiation recall pneumonitis is an uncommon treatment complication that should be correctly characterized, and it is essential to recognize the mechanisms of radiation recall pneumonitis pathogenesis and diagnostic features in order to promptly identify them and adopt the best therapeutic strategy, with the shortest possible withdrawal of the current oncological drug. In this setting, artificial intelligence could have a critical role, although a larger patient data set is required.

Immunotherapy Assessment: A New Paradigm for Radiologists

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.