Hasil untuk "Neoplasms. Tumors. Oncology. Including cancer and carcinogens"

Yingxue Guo, Yuan Wang, Fanghua Li et al.

Intraductal papillary mucinous neoplasm (IPMN) with invasive carcinoma is a rare type of pancreatic cancer that has a better prognosis than classic pancreatic infiltrating ductal carcinoma. Most distant metastases occur in the lymph nodes, lungs, liver, and bones at advanced stages. We report a rare case of an IPMN with invasive carcinoma that metastasized to the uterus, resulting in long-term survival after debulking surgery combined with hyperthermic intraperitoneal chemotherapy on a systemic treatment basis. This rare case highlights the need for oncologists and gynecologists to be vigilant regarding these uncommon metastatic diseases and exercise caution in diagnosis. Comprehensive treatments, including debulking surgery, may improve survival.

Hira Tariq, Zohaib Shahid, Sarah Ahmad et al.

Background: Cancer-related pain remains one of the most distressing and disabling symptoms experienced by patients, significantly compromising quality of life (QoL). It may arise from tumor progression, treatment-related effects, or long-term complications, affecting physical, psychological, and social well-being. Both breast cancer and lymphoma patients commonly report moderate to severe pain, yet the extent to which pain influences QoL may differ between these malignancies due to variations in disease characteristics, treatment modalities, and systemic involvement. Objective: To compare the impact of pain on quality of life among patients with breast cancer and lymphoma, with particular emphasis on differences in pain severity and associated functional outcomes. Methods: A comparative cross-sectional study was conducted in government hospitals of Lahore over a six-month period. A total of 62 patients were enrolled through purposive sampling, including 31 breast cancer and 31 lymphoma patients. Adult patients with stages I–III disease experiencing moderate to severe pain were included. Pain intensity was assessed using the Visual Analogue Scale (VAS), while quality of life was evaluated using the SF-36 questionnaire. Data were analyzed using IBM SPSS, with descriptive statistics and chi-square tests applied to determine associations between pain severity and QoL. Results: The mean age was 55.3 years in lymphoma patients and 52.6 years in breast cancer patients. The mean VAS score was 6.39 ± 1.38 for lymphoma and 6.65 ± 1.54 for breast cancer patients, with an overall mean of 6.52 ± 1.46. Poor and below-average QoL was reported in 58.7% of lymphoma patients and 80.7% of breast cancer patients. A statistically significant association between pain severity and QoL was observed in lymphoma patients (χ² = 12.45, p = 0.048), whereas no significant association was found in breast cancer patients (χ² = 9.83, p = 0.089). Conclusion: Pain demonstrated a differential impact on quality of life across cancer types, with a stronger and significant association observed in lymphoma patients. These findings underscore the need for tailored pain management strategies to improve patient-centered outcomes in oncology care. Keywords: Breast Neoplasms; Lymphoma; Neoplasm Pain; Quality of Life; Surveys and Questionnaires; Visual Analog Scale

Caio Siqueira De la Paz

Introduction: Identifying mutations in the POLE gene in endometrial cancer has direct implications for therapeutic management, potentially allowing clinicians to avoid aggressive adjuvant treatments in patients with a favorable molecular profile. Endometrial cancer is the most common gynecological neoplasm in developed countries, with a predominance of the endometrioid subtype. Recently, the molecular classification proposed by The Cancer Genome Atlas identified four distinct subtypes, including the group with POLE gene mutations, characterized by ultramutation, excellent prognosis, and low recurrence rates. Methods: A clinical case study involved a 58-year-old with high-grade endometrioid adenocarcinoma, stage IB. The patient underwent total hysterectomy, bilateral salpingo-oophorectomy, and pelvic lymphadenectomy. Genetic sequencing of the tumor confirmed the POLE mutation. The therapeutic approach was discussed at a multidisciplinary meeting, considering clinical, histopathological, and molecular data. The team decided to proceed with observation without adjuvant therapy. The patient experienced a favorable outcome post-operatively, with no evidence of disease recurrence at follow-up. Results: The POLE mutation is associated with a robust tumor immune response and excellent overall survival, even in high-grade tumors. Several studies, including ESGO/ESTRO/ESMO guidelines, recommend that patients with this molecular profile be treated with surgery alone, without the need for radiotherapy or adjuvant chemotherapy, provided there are no high-risk clinical factors. In the case analyzed, the patient had a satisfactory surgical recovery without complications. Conclusions: The molecular characterization of endometrial cancer, especially the identification of the POLE mutation, represents a significant advance in personalized treatment. In patients with this profile, such as the 58-year-old woman analyzed, a surgical approach alone may be sufficient, avoiding unnecessary toxicities and maintaining an excellent prognosis. The incorporation of genomics into clinical practice reinforces the importance of precision medicine in gynecological oncology.

Lin Zhu, Linpeng Zhang, Shuqi Han et al.

Background Gliomas represent the most prevalent primary neoplasms of the central nervous system. Activating an immune response by dendritic cells is pivotal in glioma immunotherapy. This study offers a comprehensive bibliometric analysis to elucidate the role of dendritic cells in gliomas. Method We extracted literature related to glioma and dendritic cells from 1992 to 2024 using the Web of Science Core Collection. Utilizing CiteSpace, Vosviewer and Microsoft Excel, we analyzed the volume of publications, the contributing countries/regions, institutions, authors, journals, references and keywords. Results A total of 1,576 articles were included, revealing an annual surge in dendritic cell-focused glioma research. The USA, China and Germany were the leading countries in publication output. Okada, Hideho had the most publications, while Stupp, R had the highest co-citations. Journal of Neuro-Oncology published the most articles, and Cancer Research received the highest citations. The analysis highlights pivotal themes including “dendritic cell”, “immunotherapy”, and “glioblastoma”, alongside emerging areas of interest such as “tumor microenvironment”, “immune infiltration” and “double blind”. Notably, the exploration of dendritic cell vaccinations is a key area of glioma therapeutic research, and there is growing interest in it. Conclusion This study conducts a bibliometric analysis of publications related to dendric cells in glioma. Our findings suggest that dendritic cells, immunotherapy and glioblastoma will remain the focal points and emerging trends in dendritic cell-glioma research, providing valuable insights for future studies. Dendritic cell vaccines show promise in glioma trials but are hindered by the immunosuppressive tumor microenvironment. Future work should enhance dendritic cell function and explore combination therapies to improve outcomes.

M D Ray, Manish Kumar Gaur

Abstract Introduction The nodal positivity in advanced ovarian cancers is approximately 68–70% histopathologically. Even after neoadjuvant chemotherapy (NACT) chance of nodal positivity is around 50–80%. In the prevailing literature, the nodal burden is a neglected entity in both assessment and documentation and complete clearance during the CRS. We aim to highlight the importance of nodal dissection and propose a Nodal Cancer Index (NCI) like PCI for ovarian cancers based on our experience of 105 cases. Materials and methods We included 105 patients with advanced ovarian cancers who underwent CRS. Retroperitoneal lymph nodes and bilateral pelvic lymph node dissection were routinely done in all the cases. For Nodal Cancer Index calculation, the abdomen is divided into 13 zones, zones 1–6 for retroperitoneum, zones 1–6 for Pelvic nodes, and zone 0 for extra-abdominal nodes. Furthermore, a Nodal size score ranging from 1 to 3 has been proposed so that the Nodal Cancer Index ranges from 13 to 39. Results The median age of the patients was 51 years (range 19–71) and the most significant patients were in stage III (65.7%), and 34.3% had stage IV disease at presentation. The lymph nodes were found to be positive in 62 patients (59%), and the positivity rate was higher in patients who underwent upfront surgery 36 (58.1%) as compared to 26 (41.9%) in those who received NACT. The majority of the patients (56.6%) had positive lymph nodes in both the pelvic and retroperitoneal groups, whereas 19.3% had only pelvic nodes positive, and 24.2% had only retroperitoneal nodes positive. The probability of overall survival at 5 years in our patients was 48.9% (95% CI = 35.5–61). Conclusion The results of our analytic observation confirm that systemic lymphadenectomy of all 13 zones proposed by our study should be an integral part of optimal CRS in the advanced carcinoma ovary and this will help us manage these advanced cases in a better objective manner.

Jiaoyun Zheng, Jian Gong

Due to the difficulty in early diagnosis and the lack of treatment for advanced disease, the mortality rate of hepatocellular carcinoma (HCC) is high, and the 5-year overall survival rate is low at present. SLC1A4 is a neutral amino acid transporter, but its regulatory role and mechanism in HCC are still unclear. Through analyzing the TCGA database and clinical tissue specimens, this study uncovered the high expression of SLC1A4 in tumor tissues of HCC. Worse more, a high level of SLC1A4 may lead to a poor prognosis of HCC. Mechanically, silencing SLC1A4 inhibited the phosphorylation activation of AKT by suppressing the ubiquitin modification of AKT at lysine 63 and amino acid influx represented by D-serine, decreasing the protein level of β-catenin in the cell nucleus and suppressing the transcriptional activity of c-Myc and EpCAM promoters. As a result, silencing SLC1A4 inhibited the proliferation, migration, and stemness of hepatic cancer cells, which was successfully reversed by the introduction of exogenous AKT. Moreover, epithelial–mesenchymal transition (EMT) in vitro and metastasis potential in vivo of hepatic cancer cells was suppressed by the downregulated SLC1A4 level. In conclusion, SLC1A4 promotes the malignant transformation of HCC through activating signal transduction mediated by AKT. The findings in this study suggested that SLC1A4 may be a diagnostic indicator for the early HCC and a therapeutic target for the advanced HCC.

Ruijun Guo, Jiajun Xu, Chunxia Li et al.

Abstract Objective Tumor-derived exosomes testing can be effective in diagnosing disease and assisting in the treatment of disease. Our study utilizes bibliometric analysis to identify research hotspots related to tumor-derived exosomes, predict emerging research frontiers and development trends, and offer diverse perspectives for advancing research in this field. Methods Search the Web of Science Core Collection for English-language literature published on the field of tumor-derived exosomes from 2015 to 2024. CiteSpace(6.2.R3) software was utilized to visualize the distribution of countries/regions, institutions, authors, co-cited authors, and co-cited journals within the relevant literature. Additionally, co-occurrence, clustering, and emergence analyses were conducted on the co-cited references. Results An analysis of 2523 articles meeting the inclusion criteria revealed a steady increase in the number of publications in this field over the past decade. In terms of countries/regions, institutions, authors, and journals that published articles, the most productive were China, Ministry of Education-China, Theresa L. Whiteside, and CANCER RES, respectively. The most influential were The United States, Harvard University, Theresa L. Whiteside, and CANCER RES, respectively. The mechanisms underlying exosomal PD-L1 and engineered exosomes are currently prominent research foci, warranting meticulous examination by the academic community. Conclusion Within the field of research on tumor-derived exosomes, current investigations appear largely concentrated on the exosome PD-L1 mechanism and engineered exosomes. Possible future research hotspots will focus on the use of engineered exosomes to target tumor cells and as a drug delivery platform for more precise therapeutic targeting.

Qineng Gong, Tianyu Zhu, Linlin Zhang et al.

Abstract Hepatocellular carcinoma (HCC) is a predominant form of liver cancer and one of the leading causes of cancer-related death globally. Therefore, there is an urgent need for innovative therapeutic strategies that target the molecular mechanisms underlying HCC progression and metastasis, aiming to improve treatment efficacy and patient survival. The natural product celastrol (Cel) has demonstrated inhibitory effects in various cancer cell lines. However, its clinical application has been hindered by high toxicity and a low safety threshold. Metal-free quantum dots (QDs), AgInS2 (AIS QDs) not only eliminate toxic risks associated with heavy metals but also exhibit high biocompatibility in the biomedical field. By developing AIS QD@Cel, an AIS QDs nano-delivery system for Cel, the cell selectivity and inhibitory effects of Cel on HCC were enhanced. Fourier-transform infrared spectroscopy (FTIR) analysis revealed that AIS QDs can interact with Cel via amide bonds. The encapsulation rate of AIS QDs to Cel reached 27.5%. AIS QD@Cel eliminated toxicity on 293T and enhanced inhibition on HCC cells by over 10 times. Furthermore, the western blotting and flow cytometry experiments showed that AIS QD@Cel promoted apoptosis and autophagy signal pathway. Finally, transcriptome sequencing revealed that AIS QD@Cel effect on HCC by regulating gene expression involved in critical signaling pathways that are implicated in the progression of cancer. This strategy holds the potential to increase safety threshold and clinical applicability of Cel, offering significant clinical value for the treatment of HCC patients.

Michael Kapteyn, Anirban Chaudhuri, Ernesto A. B. F. Lima et al.

Background: Advances in the theory and methods of computational oncology have enabled accurate characterization and prediction of tumor growth and treatment response on a patient-specific basis. This capability can be integrated into a digital twin framework in which bi-directional data-flow between the physical tumor and the digital tumor facilitate dynamic model re-calibration, uncertainty quantification, and clinical decision-support via recommendation of optimal therapeutic interventions. However, many digital twin frameworks rely on bespoke implementations tailored to each disease site, modeling choice, and algorithmic implementation. Findings: We present TumorTwin, a modular software framework for initializing, updating, and leveraging patient-specific cancer tumor digital twins. TumorTwin is publicly available as a Python package, with associated documentation, datasets, and tutorials. Novel contributions include the development of a patient-data structure adaptable to different disease sites, a modular architecture to enable the composition of different data, model, solver, and optimization objects, and CPU- or GPU-parallelized implementations of forward model solves and gradient computations. We demonstrate the functionality of TumorTwin via an in silico dataset of high-grade glioma growth and response to radiation therapy. Conclusions: The TumorTwin framework enables rapid prototyping and testing of image-guided oncology digital twins. This allows researchers to systematically investigate different models, algorithms, disease sites, or treatment decisions while leveraging robust numerical and computational infrastructure.

Xinhai Hou, Akhil Kondepudi, Cheng Jiang et al.

The importance of rapid and accurate histologic analysis of surgical tissue in the operating room has been recognized for over a century. Our standard-of-care intraoperative pathology workflow is based on light microscopy and H\&E histology, which is slow, resource-intensive, and lacks real-time digital imaging capabilities. Here, we present an emerging and innovative method for intraoperative histologic analysis, called Intelligent Histology, that integrates artificial intelligence (AI) with stimulated Raman histology (SRH). SRH is a rapid, label-free, digital imaging method for real-time microscopic tumor tissue analysis. SRH generates high-resolution digital images of surgical specimens within seconds, enabling AI-driven tumor histologic analysis, molecular classification, and tumor infiltration detection. We review the scientific background, clinical translation, and future applications of intelligent histology in tumor neurosurgery. We focus on the major scientific and clinical studies that have demonstrated the transformative potential of intelligent histology across multiple neurosurgical specialties, including neurosurgical oncology, skull base, spine oncology, pediatric tumors, and periperal nerve tumors. Future directions include the development of AI foundation models through multi-institutional datasets, incorporating clinical and radiologic data for multimodal learning, and predicting patient outcomes. Intelligent histology represents a transformative intraoperative workflow that can reinvent real-time tumor analysis for 21st century neurosurgery.

Marcela V. Reale, Gustavo Paccosi, David H. Margarit et al.

Understanding cancer cell differentiation is essential for advancing its detection, diagnosis, and treatment. Mathematical models significantly contribute to this by providing a theoretical framework to understand the complex interactions between cancer stem cells, differentiated cancer cells, and immune system components. Such models depend on experimental data and computational simulations to predict tumor dynamics, offering insights into how different cell populations evolve over time. However, to ensure their realistic and consistent outcomes, rigorous mathematical analysis is required, including verification of solution uniqueness, stability, viability, positivity, and boundedness. Such validation guarantees that model's results can be used in both oncological research and clinical applications. In this study, we conduct a comprehensive analysis of an integrative mathematical model of cancer cell differentiation, with a particular focus on its interactions with immune cells. The model captures the dynamic balance between cancer stem cell self-renewal, differentiation into mature tumor cells, and immune-mediated elimination. By employing analytical and numerical techniques, we assess the model's feasibility, stability, and long-term behavior under various biological conditions. Our findings demonstrate that immune system engagement can significantly influence tumor composition and growth, highlighting potential therapeutic targets. This work not only advances theoretical cancer modeling but also provides a foundation for future experimental validation and the development of combined differentiation-immunotherapy approaches. The results underscore the importance of interdisciplinary collaboration in the fight against cancer.

Lydia Jang, Stefan Konigorski

The effectiveness of personalized oncology treatments ultimately depends on whether outcomes can be causally attributed to the treatment. Advances in precision oncology have improved molecular profiling of individuals, and tailored therapies have led to more effective treatments for select patient groups. However, treatment responses still vary among individuals. As cancer is a heterogeneous and dynamic disease with varying treatment outcomes across different molecular types and resistance mechanisms, it requires customized approaches to identify cause-and-effect relationships. N-of-1 trials, or single-subject clinical trials, are designed to evaluate individual treatment effects. Several works have described different causal frameworks to identify treatment effects in N-of-1 trials, yet whether these approaches can be extended to single-cancer patient settings remains unclear. To explore this possibility, a longitudinal dataset from a single metastatic cancer patient with adaptively chosen treatments was considered. The dataset consisted of a detailed treatment plan as well as biomarker and lesion measurements recorded over time. After data processing, a treatment period with sufficient data points to conduct causal inference was selected. Under this setting, a causal framework was applied to define an estimand, identify causal relationships and assumptions, and calculate an individual-specific treatment effect using a time-varying g-formula. Through this application, we illustrate explicitly when and how causal treatment effects can be estimated in single-patient oncology settings. Our findings not only demonstrate the feasibility of applying causal methods in a single-cancer patient setting but also offer a blueprint for using causal methods across a broader spectrum of cancer types in individualized settings.

Chenghang Li, Jinzhi Lei

Mathematical oncology is a rapidly evolving interdisciplinary field that uses mathematical models to enhance our understanding of cancer dynamics, including tumor growth, metastasis, and treatment response. Tumor-immune interactions play a crucial role in cancer biology, influencing tumor progression and the effectiveness of immunotherapy and targeted treatments. However, studying tumor dynamics in isolation often fails to capture the complex interplay between cancer cells and the immune system, which is critical to disease progression and therapeutic efficacy. Mathematical models that incorporate tumor-immune interactions offer valuable insights into these processes, providing a framework for analyzing immune escape, treatment response, and resistance mechanisms. In this review, we provide an overview of mathematical models that describe tumor-immune dynamics, highlighting their applications in understanding tumor growth, evaluating treatment strategies, and predicting immune responses. We also discuss the strengths and limitations of current modeling approaches and propose future directions for the development of more comprehensive and predictive models of tumor-immune interactions. We aim to offer a comprehensive guide to the state of mathematical modeling in tumor immunology, emphasizing its potential to inform clinical decision-making and improve cancer therapies.

Peace Chinonyerem Ike, Victor Ifechukwude Agboli, ONYEBUKWA ANTHONY KELECHI et al.

Shaping the universe of the Internet of Things (IoT) means rewriting how cancer treatment is given to patients. Research approach followed in this study is based on the comprehensive examination of IoT in carrying out cancer interventions through its part of real-time data collection and processing. Genetic predisposition determines cancer. Nevertheless, it is primarily unscrupulous management of such determinants in preventive care. IoT wearables and health monitoring wearables take pictures and allow continuous tracking of high-risk patients for cancer so that any deviation can activate proper preventive measures. Based on what is now understood, healthcare professionals stop the route of mere treatment of disease and rearrange their models into more and more predictive ones. Along the way, with the development of these devices, it becomes possible for the genetic mutation and the biomarker to be monitored in real-time. Lifestyle risk factors are mostly linked with cancer growth and development, including diet, activity, and exposure to carcinogens. IoT devices with wearable sensors and mobile health apps can define to patients exactly how active they are and the behaviours they are in their environment. For instance, air pollution sensors can detect an amount of pollutants that are linked to lung cancer, and fitness trackers can incentivize behavior as safety procedures. Such a change raises consumer engagement, which fosters the development of improved practices and reduction in risk factors. The unique characteristic of IoT in oncology, direct monitoring, provides real-time and constant feedback of various physiological states of the patients. Smart implants and biosensors are among the networked devices that generate real-time information about tumors, efficacy of treatment, and side effects. With this constantly growing amount of data, strategic planning is enhanced so that the treatment programs can be modified more effectively and accurately. Real-time monitoring enables deviation from the conventional cancer treatment to more sophisticated medicine, under strict monitoring and observation of any genetic hazards and lifestyle habits. The approach results in improved clinical outcomes and allows patients to take an active role in the self-management of their health. With the development of such IoT technologies, there is unlimited potential for revolutionizing the prevention and treatment of cancer, ultimately paving the way for the future of personalized, preventive, and patient-centered oncology.

Background: Cancer-associated thrombotic microangiopathy (CA-TMA) is a rare but severe complication of malignancy characterized by microangiopathic hemolytic anemia (MAHA), thrombocytopenia, and organ dysfunction, typically in the absence of thrombotic thrombocytopenic purpura (TTP)-defining ADAMTS13 deficiency. Its pathophysiology is poorly understood, but it is hypothesized to involve direct endothelial injury by tumor cells, cytokine-mediated microvascular damage, or tumor-related procoagulant activity. Most cases of CA-TMA have been reported in patients with mucin-producing adenocarcinoma (e.g. gastric, breast cancer) and in those with disseminated malignancies, but also described in cases with isolated invasion of the bone marrow. Treatment primarily focuses on controlling the underlying malignancy; plasma exchange (PEX) and steroids, commonly used in TTP, are generally ineffective in CA-TMA. Prognosis remains poor, often due to advanced-stage malignancy and limited responsiveness to oncologic treatment. Prompt recognition and accurate diagnosis, including consideration of bone marrow biopsy (BMB), are critical for optimal management. Case Report: We present two very similar cases of CA-TMA referred to our Department. The main clinical characteristics and laboratory findings of the patients are summarized in Table 1. In both cases, laboratory tests performed in the Emergency Department (ED) revealed severe thrombocytopenia and MAHA, so they were admitted to our Centre under the suspicion of TTP, and PEX and corticosteroids were initiated while awaiting ADAMTS13 activity results; in light of the normal levels of ADAMTS13 activity, TTP was ruled out and PEX discontinued; further investigation was pursued to identify alternative causes of TMA. In Case 1 a total-body CT scan and a colonoscopy were performed and found to be essentially unremarkable. In Case 2, a total-body CT scan, initially performed to rule out pulmonary embolism, revealed sternal osteolytic lesions and recent left rib fractures (she reported a recent car accident). Consequently, a PET-CT scan was obtained, showing widespread skeletal hypermetabolism. Given the non-definitive clinical presentation, both patients underwent BMB which revealed diffuse osteomedullary metastases of epithelial malignant neoplasm consistent with breast cancer, confirming the diagnosis of CA-TMA. Both patients were transferred to the Oncology Department to initiate chemotherapy, but despite rapid intervention, both patients died within 40 days (Case 1) and 6 days (Case 2) from admission. Conclusions: CA-TMA is a life-threatening but often underrecognized manifestation of malignancy. CA-TMA does not respond to PEX or immunosuppressive therapy, for this reason early identification and differentiation from other TMAs, especially TTP, are essential. Diagnosis requires clinical suspicion and comprehensive evaluation, including imaging and BMB, especially when other diagnostic findings are inconclusive. Our cases highlight the critical role of early BMB in establishing diagnosis and initiating appropriate oncologic treatment. Literature review confirms the limited efficacy of supportive therapy alone and underscores the urgent need for targeted cancer therapy in improving survival. A multidisciplinary approach and awareness of CA-TMA in patients with known or suspected malignancy presenting with MAHA and thrombocytopenia can significantly influence diagnostic timelines and therapeutic strategies.

Shiting Li, Shaomiao Xia, Maria Lawas et al.

HPV integration (HPVint) is associated with carcinogenesis and tumor progression in HPV-associated cancers, including head and neck squamous cell carcinomas (HNSCC). While its impact on human DNA has been well characterized, its relationship with clinical outcomes remains unconfirmed. Here we investigate the consequences of HPVint both with respect to human and HPV characteristics by analyzing 261 HPV-associated HNSCC bulk and single-cell RNA-seq samples from five cohorts, and DNA HPVint events from 102 HPV+ participants in two of the cohorts. By leveraging this large meta-cohort, we first reveal an oncogenic network based on the recurrent HPV integration locations in HNSCC. We then classify HPVint-positive (HPVint(+)) participants by HPV RNA features, specifically based on spliced HPV-human fusion transcripts and ratios of HPV gene transcripts, showing that subsets of participants have worse clinical outcomes. Our analyses, focused mainly on RNA instead of DNA, expand our understanding of the carcinogenic mechanisms of HPVint, partially addressing the conflicting findings of whether HPVint is associated with aggressive phenotypes and worse clinical consequences, and provide potential biomarkers to advance precision oncology in HPV-associated HNSCC.

Shiting Li, Shaomiao Xia, Maria Lawas et al.

PURPOSE HPV integration (HPVint) is associated with carcinogenesis and tumor progression in HPV-associated cancers, including head and neck squamous cell carcinomas (HNSCC). While its impact on human DNA has been well characterized, its relationship with clinical outcomes remains unconfirmed. EXPERIMENTAL DESIGN We analyzed HPVint events from 261 HPV-associated HNSCC bulk and single-cell RNA-seq samples from five cohorts, including 62 from a new University of Michigan cohort, and DNA HPVint events from 102 HPV(+) HNSCC participants in two of the cohorts. We investigated the consequences of HPVint both with respect to human and HPV gene expression and clinical outcomes (recurrence and overall survival). RESULTS By leveraging this large meta-cohort of HNSCC, we first reveal an oncogenic gene network based on the recurrent HPV integration locations in the human genome and gene expression alterations, highlighting key recurrent and overexpressed genes including NR4A2, CD274, CCER1 and genes from the CAMK and KLF families. We then stratify HPVint-positive participants by risk using HPV RNA features, specifically spliced HPV-human fusion transcripts (E1* integration) and HPV gene expression ratios (HGER), showing that subsets of participants have worse clinical outcomes based on these two candidate biomarkers. CONCLUSIONS By focusing on RNA instead of DNA, we expand our understanding of the carcinogenic mechanisms of HPVint, in part addressing the conflicting findings of whether HPVint is associated with aggressive phenotypes and worse clinical consequences and provide potential biomarkers to advance precision oncology in HPV-associated HNSCC. Newly identified genes with recurrent integration events may serve as candidates for targeted therapy.

Assia Hijazi, Jérôme Galon

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients’ response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.

Maxime Ronot, M. Dioguardi Burgio, Jules Grégory et al.

Neuroendocrine tumors (NETs) are relatively rare neoplasms displaying heterogeneous clinical behavior, ranging from indolent to aggressive forms. Patients diagnosed with NETs usually receive a varied array of treatments, including somatostatin analogs, locoregional treatments (ablation, intra-arterial therapy), cytotoxic chemotherapy, peptide receptor radionuclide therapy (PRRT), and targeted therapies. To maximize therapeutic efficacy while limiting toxicity (both physical and economic), there is a need for accurate and reliable tools to monitor disease evolution and progression and to assess the effectiveness of these treatments. Imaging morphological methods, primarily relying on computed tomography (CT) and magnetic resonance imaging (MRI), are indispensable modalities for the initial evaluation and continuous monitoring of patients with NETs, therefore playing a pivotal role in gauging the response to treatment. The primary goal of assessing tumor response is to anticipate and weigh the benefits of treatments, especially in terms of survival gain. The World Health Organization took the pioneering step of introducing assessment criteria based on cross-sectional imaging. This initial proposal standardized the measurement of lesion sizes, laying the groundwork for subsequent criteria. The Response Evaluation Criteria in Solid Tumors (RECIST) subsequently refined and enhanced these standards, swiftly gaining acceptance within the oncology community. New treatments were progressively introduced, targeting specific features of NETs (such as tumor vascularization or expression of specific receptors), and achieving significant qualitative changes within tumors, although associated with minimal or paradoxical effects on tumor size. Several alternative criteria, adapted from those used in other cancer types and focusing on tumor viability, the slow growth of NETs, or refining the existing size-based RECIST criteria, have been proposed in NETs. This review article aims to describe and discuss the optimal utilization of CT and MRI for assessing the response of NETs to treatment; it provides a comprehensive overview of established and emerging criteria for evaluating tumor response, along with comparative analyses. Molecular imaging will not be addressed here and is covered in a dedicated article within this special issue.