Mihai Vasile Marinca

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a common, disabling toxicity with no validated biomarkers. MRI-based functional neuroimaging could offer insight into central pain processing and may reveal reproducible brain signatures of CIPN. Methods: Following PRISMA 2020 (PROSPERO: CRD420251132102), we systematically reviewed whole-brain MRI studies in adult cancer patients with CIPN. Eligible MRI techniques included task-based fMRI, resting-state fMRI, perfusion MRI, and structural MRI. Data were synthesized through voxelwise activation likelihood estimation (ALE), systems-level region-of-interest (ROI) mapping, and proportion meta-analysis of regional involvement. Results: Of 2488 screened records, five observational studies were included. The voxelwise ALE analysis did not identify clusters surviving correction, but dispersed foci appeared within the default mode network (DMN), prefrontal executive cortex, and primary sensorimotor regions, suggesting the engagement of these pain-processing networks. ROI synthesis confirmed consistent alterations in the DMN and executive prefrontal and sensorimotor cortices in CIPN patients compared with controls, while the brainstem/periaqueductal gray and cerebellum were rarely implicated. Proportion meta-analysis further quantified these differences: CIPN patients showed altered involvement in 30% (95% CI 0.16–0.48) of contrasts, with the highest frequencies in the DMN (50%), sensorimotor (33%), and executive prefrontal regions (33%). By contrast, control-higher contrasts were less frequent (10%, 95% CI 0.03–0.27), highlighting CIPN-related increases particularly in self-referential and somatosensory networks. Conclusions: Across analytic approaches, CIPN is characterized by reproducible alterations in the DMN and executive prefrontal and sensorimotor networks. These central pain signatures represent promising MRI-based biomarkers for identifying and monitoring CIPN in oncology.

Background: Rituximab, a monoclonal antibody targeting CD20, has revolutionized the management of B-cell lymphoproliferative disorders and some immune conditions, significantly improving disease control and patient survival. Beyond its indisputable therapeutic benefits, rituximab can cause serious pulmonary adverse events, particularly interstitial lung disease (R-ILD). Diagnosing R-ILD is challenging due to nonspecific clinical and imagistic features, and its true incidence is possibly underestimated. Methods: We conducted a systematic review to synthesize current evidence on R-ILD, focusing on its incidence, diagnostic approaches, management strategies and clinical outcomes. A comprehensive search of PubMed/MEDLINE was performed using the term “rituximab induced interstitial lung disease” through August 2025. Relevant abstracts were screened, and full-text articles meeting the inclusion criteria were analyzed. Results: A total of 40 studies were retained after the search and screening, including case reports, case series and cohort studies of R-ILD. This condition was identified in both malignant and autoimmune disorders receiving rituximab, more frequently for combination regimens. Radiological manifestations were heterogeneous, and ground-glass opacities were the dominant pattern. Most R-ILD cases were reversible, but progression to chronic interstitial disease and fatal outcomes are possible. Cohort studies demonstrated variability in incidence, reported instances of successful rituximab reintroduction and suggested a protective effect of prophylactic trimethoprim-sulfamethoxazole against opportunistic pneumonitis. Conclusions: Although rare, R-ILD is a clinically significant complication of rituximab therapy. Early recognition and multidisciplinary management are essential, as most patients respond to corticosteroids, while severe cases may progress to respiratory failure or fatal outcomes.

Background and Objectives: Cancer pain continues to be a major clinical problem nowadays. This study aims to evaluate the World Health Organization (WHO) analgesic ladder effectiveness in patients with colorectal cancer and develop machine learning models to predict treatment response for precision pain management. Materials and Methods: In a retrospective observational study, a total of 107 oncological patients were analyzed, with a detailed subgroup analysis of 42 patients with colorectal cancer, hospitalized between July and September in 2022. The pain assessment used numerical rating scales at baseline and 2–3 weeks follow-up. Clinical variables included demographics, disease staging, metastatic patterns, analgesic progression, and medication usage. Machine learning algorithms (e.g., Random Forest, CatBoost, XGBoost, and Neural Network) were used to predict pain reduction outcomes. The UMAP dimensionality reduction and clustering identified the patient phenotypes. Results: Statistical analyses included descriptive methods, Chi-square and Mann–Whitney tests, and the models’ performance was evaluated by AUC. Among patients with colorectal cancer, 73.8% achieved clinically pain improvement, with a mean reduction of 2.62 points and median improvement of 3.00 points. The metastatic site significantly affected outcomes: visceral metastases patients showed median improvement of 3.00 points with high variability, patients with bone metastases demonstrated heterogeneous responses (range: −2.00 to +8.00 points), while non-metastatic patients exhibited consistent improvement. Random Forest achieved optimal predictive performance (AUC: 0.9167), identifying the baseline pain score, bone metastases, Fentanyl usage, anticonvulsants, and antispasmodics as key predictive features. The clustering analysis revealed two distinct phenotypes, requiring different analgesic intensities. Conclusions: This study validates the WHO analgesic ladder effectiveness while demonstrating superior outcomes in patients with colorectal cancer. The machine learning models successfully predict the treatment response with excellent discriminative ability, supporting precision medicine implementation in cancer pain management.

Aberrant activation of proangiogenic signaling pathways, particularly the vascular endothelial growth factor (VEGF) axis, drives neovascularization and tumor progression in colorectal cancer (CRC). Bevacizumab targets VEGF-A-mediated angiogenesis, but the lack of validated predictive biomarkers limits personalized treatment. In this prospective study, we evaluated a panel of circulating angiogenic biomarkers combined with clinical parameters, using mathematical models to predict survival in metastatic CRC patients treated with bevacizumab and chemotherapy. Low VEGF-A and VEGF-D levels, together with high bFGF, were associated with improved overall survival (OS). A logistic regression model incorporating these biomarkers, regional lymph node invasion, and primary tumor resection status showed significant prognostic accuracy (p < 0.001). Incorporating CypA further refined the model, identifying patients with low VEGF-A, VEGF-D, and CypA, and high VEGF-C and PlGF, as having the most favorable OS. These findings demonstrate that integrating clinical and circulating biomarker data can improve individualized risk assessment and support personalized therapeutic strategies for CRC patients receiving bevacizumab.

Introduction: Metastatic colorectal cancer (mCRC) is a disease with various molecular profiles that exhibit different evolution patterns. Although most mCRC patients receive the same chemotherapy drugs in the first-line setting, treatment response is heterogeneous suggesting some tumors are inherently resistant to oxaliplatin/fluoropyrimidine regimen. Genomic-based markers may help identify these patients and guidetreatment decisions due to potential prognostic and predictive value.Methods: We performed a retrospective analysis on 77 patients diagnosed with mCRC treated with an oxaliplatin/fluoropyrimidine regimen in the Regional Institute of Oncology Iaşi between April 2017 and December 2019. We studied the impact of KRAS, NRAS, BRAF, PIK3CA and TP53 genes and their mutations in a treatment-naive population.Results: The median progression free survival (PFS) was 11 months (95% CI, 10.2-11.7 months) and the median overall survival (OS) was 23.6 months (16.3-30.8 months). Multivariate analysis of factors affecting PFS revealed that KRAS exon –3 mutation was associated with quicker progression while on oxaliplatin-based chemotherapy. A similar analysis indicated that the KRAS exon –3 mutation was also associated with decreased OS (p=0.03). The presence of the TP53 in exon 8 was associated with an increased OS (p=0.001).Discussion: The present analysis offers insights into the prognostic implications of genes and exon-distributed mutations within RAS, BRAF, PIK3CA, and TP53 in mCRC. Subsequent prospective investigations with a more extensive patient cohort are needed to clarify the influence of exon-distributed mutations on therapeutic decision-making and prognostic outcomes.

Background: Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and to determine the specific attributes that influence the presence of treatment-related side effects. Methods: The predictor was general toxicity, and for the construction of our data training, we selected 95 characteristics that represent the health state of 74 patients prior to their first round of chemotherapy. After the data were processed, Random Forest models were trained to offer an optimal balance between accuracy and interpretability. Results: We constructed a machine learning predictor with an emphasis on assessing the importance of numerical and categorical variables in relation to toxicity. Conclusions: The incorporation of artificial intelligence in personalizing colorectal cancer management by anticipating and overseeing toxicities more effectively illustrates a pivotal shift towards more personalized and precise medical care.

Ovarian cancer is one of the most frequent malignancies in women. The treatment landscape underwent significant changes as new agents were introduced in ovarian cancer management over the last decade. We present two cases of long responses to Olaparib in BRCA (BReast CAncer gene) mutant ovarian cancer patients. The first case belongs to a 42-year-old female diagnosed with advanced ovarian carcinoma with a rare germinal mutation (BRCA1 c.68_69delAG, commonly found in descendants of Ashkenazi Jewish populations, but also Arabic and Asian ones) and a significant family history of ovarian and breast cancers. After poorly tolerated neoadjuvant chemotherapy, the patient underwent total hysterectomy, bilateral adnexectomy, and intraperitoneal hyperthermic chemotherapy. After eight months, the disease progressed, and first-line platinum chemotherapy was administered. Although not well-tolerated (grade 3 anemia, allergic reactions), chemotherapy resulted in a partial response, and given the patient’s characteristics, maintenance with Olaparib was recommended. Treatment is ongoing (total current duration 69 months) and tolerated well (grade 1 side effects). This case illustrates the long-term benefits that novel therapies like Olaparib may offer in patients with platinum-sensitive relapsed ovarian cancer harboring a rare BRCA mutation. The second case highlights a 55-year-old postmenopausal woman diagnosed with ovarian cancer, FIGO stage IVA. Initial treatment included six cycles of chemotherapy, which led to a partial response, followed by interval debulking surgery and another four cycles of chemotherapy. Subsequent Olaparib maintenance therapy post BRCA1 mutation identification contributed to a significant progression-free survival of 65 months until disease recurrence and secondary cytoreductive surgery, showcasing the effectiveness of PARP inhibitors in personalized oncology treatment of ovarian cancer.

Colorectal cancer (CRC) ranks as second most common cause of cancer-related deaths. The CRC management considerably improved in recent years, especially due to biological therapies such as bevacizumab. The lack of predictive or prognostic biomarkers remains one of the major disadvantages of using bevacizumab in the CRC management. We performed a prospective study to analyze the prognostic and predictive roles of three potential serum biomarkers (Cyclophilin A (CypA), copeptin and Tie2) investigated by ELISA in 56 patients with metastatic CRC undergoing bevacizumab and chemotherapy between May 2019 and September 2021 at baseline and after one and six months of therapy. We showed that low levels of CypA at baseline and after one month of treatment were associated with better overall survival (OS) (42 versus 24 months, p = 0.029 at baseline; 42 versus 25 months, p = 0.039 after one month). For copeptin and Tie2, Kaplan–Meier curves showed no correlation between these biomarkers and OS or progression-free survival. When adjusting for baseline and post-treatment factors, a multivariate Cox analysis showed that low values of CypA at baseline and after one month of treatment were independent prognostic factors for OS and correlated with a better prognosis in metastatic CRC patients.

Mutations in RAS, BRAF, PIK3CA, and TP53 are well-established genetic abnormalities in metastatic colorectal cancer (mCRC). However, limited information is available for patients from Eastern Europe, including Romania. In this retrospective analysis, we investigated 104 mCRC patients from the Northeastern region of Romania to determine the frequency, distribution, coexistence, and clinicopathological and molecular correlations of these mutations. TP53 was the most frequently mutated gene (73.1%), followed by KRAS (45.2%) and PIK3CA (6.7%). Patients with KRAS mutant tumors and wild-type TP53 genotype were found to have no personal history of gastrointestinal cancer (p = 0.02, p = 0.007). KRAS mutations in exon 3 were associated with the female gender (p = 0.02) and the absence of lymph node invasion (p = 0.02). PIK3CA mutations were linked to the absence of lymph node invasion (p = 0.006). TP53 mutations were associated with KRAS mutations in exon 2 (p = 0.006), ulcerated histopathologic type (p = 0.04), and G2 differentiation (p = 0.01). It provides novel insights into genetic variations specific to the population from Northeastern Romania, which has been underrepresented in previous studies within Eastern Europe. Furthermore, our findings enable the development of genetic profiles in a developing country with limited access to specialized genetic tests and facilitate comparisons with other populations.

Lung cancer remains a major public health problem both in terms of incidence and specific mortality despite recent developments in terms of prevention, such as smoking reduction policies and clinical management advances. Better lung cancer prognosis could be achieved by early and accurate diagnosis and improved therapeutic interventions. Nanotechnology is a dynamic and fast-developing field; various medical applications have been developed and deployed, and more exist as proofs of concepts or experimental models. We aim to summarize current knowledge relevant to the use of nanotechnology in lung cancer management. Starting from the chemical structure-based classification of nanoparticles, we identify and review various practical implementations roughly organized as diagnostic or therapeutic in scope, ranging from innovative contrast agents to targeted drug carriers. Available data are presented starting with standards of practice and moving to highly experimental methods and proofs of concept; particularities, advantages, limits and future directions are explored, focusing on the potential impact on lung cancer clinical prognosis.