Pharmacogenomics and Big Data in medical oncology: developments and challenges.

Medical oncology, through conventional chemotherapy as well as targeted drugs, remains an important component of cancer patient management, particularly for systemic disease. Despite advances in all areas of medical oncology, certain challenges persist in the form of drug resistance and severe normal tissue toxicity. These unwanted effects can be counteracted through a patient-tailored treatment approach, which in chemotherapy is translated as pharmacogenomics. This research field investigates the way genetic makeup influences a patient's response to various drugs with the aim to minimize trial-and-error associated with drug administration. The paper introduces the role, advances and challenges of pharmacogenomics, highlighting the importance of Big Data mining to reveal the mechanisms behind drug-gene pair interaction for better patient outcomes. International consortiums have prioritized their focus on the clinical implementation of pharmacogenomics while tackling the challenges ahead: data standardization, ethical aspects and the education of physicians and patients alike to comprehend the power of pharmacogenomics to transform medical oncology.

Drug-gene interaction and implications for medical oncology Pharmacogenomics is a research field that investigates the way the genetic makeup influences a patient's response to various drugs with the aim to minimise trial-and-error associated with drug administration. This overview of state-of-the-art research introduces the role, advances, and challenges of pharmacogenomics, highlighting the importance of Big Data mining to reveal the mechanisms behind drug-gene pair interaction for better patient outcome.

Expected benefits and concerns regarding virtual reality in caring for terminally ill cancer patients - a qualitative interview study.

BACKGROUND: Many palliative cancer patients require inpatient hospital treatment for medical reasons, which contrasts their frequent desire to be at home. Virtual reality (VR) could be a way of bringing the home environment closer to them. First observations have shown benefits from VR for inpatients in palliative care. The aim of this qualitative, descriptive study was to explore the expectations of in-patients suffering from incurable cancer and their relatives about VR, in particular individualized VR images of the patients' own home. METHODS: Semi-structured interviews with inpatients suffering from incurable cancers and their relatives in three medical settings (palliative care, hematology, radiotherapy) of a German university hospital. Qualitative content analysis about expected benefits and concerns regarding VR-videos showing their private home; defining the main topics deductively and the subcategories inductively. We also assessed the patients' subjective perspective on their remaining time to live to estimate the impact of double awareness on the results. The Patient Advisory Board informed the study protocol and conduct. RESULTS: We interviewed 15 patients (8 men; age M = 63.4, SD = 11.34; range 39-82) under palliative care, and four relatives. We organized the interview content in 6 themes (general interest, desired content, non-desired content, expected benefits, concerns, and irregularities) and 26 sub-themes. Most patients and relatives were interested in using VR during hospital treatment. They often preferred viewing nature or tourist sites over seeing their home or family. Reasons could be linked to privacy concerns and the general desire for distraction from the current situation that they specified with their expectation of well-being, a break from the patient-experience, the pursue of curiosity, and the VR evoking fond memories. CONCLUSION: VR seems to be of interest for palliative cancer patients, especially as distraction and relief from their illness. The desired content can be very different, so a choice from a selection of VR-content should be made available. If patients want to see videos of their own home, recordings by relatives instead of study or hospital staff seem to meet the need for privacy. TRIAL REGISTRATION: Registered at Deutsches Register Klinischer Studien; registration number: DRKS00032172; registration date: 11/07/2023. https://drks.de/search/de/trial/DRKS00032172.

In vitro testing of drug response in primary multiple myeloma cells using a microwell-based technology.

Multiple myeloma is an aggressive neoplasm of plasma cells. While numerous drugs have gained approval, the absence of established predictive markers for individual drug responses poses a challenge. In this study, we explored the microwell- and fluorescence-based Cellply CC-Array® technology for high-throughput analysis of in vitro drug responses as a potential predictive marker for patient treatment outcomes. Furthermore, we investigated its application for evaluating effector cell effectiveness. Mononuclear cells were isolated from the bone marrow of 22 patients, and in vitro drug response of primary myeloma cells was analyzed. In vitro responses towards melphalan, bortezomib, and dexamethasone in primary patient samples correlated with clinical response of the patients. The approach exhibited limitations in identifying sensitivity towards lenalidomide, daratumumab, and elotuzumab due to limited culturing time caused by poor myeloma viability in vitro. Through the analysis of cell proximity, the platform enabled the assessment of individual anti-tumor activity from NK and T cells. In summary, the CC-Array microwell technology allowed assessment of myeloma cell responses to selected drugs used in multiple myeloma therapy in vitro. To further validate these in vitro results against in vivo outcomes, screening a larger cohort is necessary.

Recent progress and applications of single-cell sequencing technology in breast cancer.

Single-cell RNA sequencing (scRNA-seq) technology enables the precise analysis of individual cell transcripts with high sensitivity and throughput. When integrated with multiomics technologies, scRNA-seq significantly enhances the understanding of cellular diversity, particularly within the tumor microenvironment. Similarly, single-cell DNA sequencing has emerged as a powerful tool in cancer research, offering unparalleled insights into the genetic heterogeneity and evolution of tumors. In the context of breast cancer, this technology holds substantial promise for decoding the intricate genomic landscape that drives disease progression, treatment resistance, and metastasis. By unraveling the complexities of tumor biology at a granular level, single-cell DNA sequencing provides a pathway to advancing our comprehension of breast cancer and improving patient outcomes through personalized therapeutic interventions. As single-cell sequencing technology continues to evolve and integrate into clinical practice, its application is poised to revolutionize the diagnosis, prognosis, and treatment strategies for breast cancer. This review explores the potential of single-cell sequencing technology to deepen our understanding of breast cancer, highlighting key approaches, recent advancements, and the role of the tumor microenvironment in disease plasticity. Additionally, the review discusses the impact of single-cell sequencing in paving the way for the development of personalized therapies.

Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using 18F-FDG PET/CT Imaging: Contribution of Artificial Intelligence and Radiomics Analysis.

Lymphoma, encompassing a wide spectrum of immune system malignancies, presents significant complexities in its early detection, management, and prognosis assessment since it can mimic post-infectious/inflammatory diseases. The heterogeneous nature of lymphoma makes it challenging to definitively pinpoint valuable biomarkers for predicting tumor biology and selecting the most effective treatment strategies. Although molecular imaging modalities, such as positron emission tomography/computed tomography (PET/CT), specifically 18F-FDG PET/CT, hold significant importance in the diagnosis of lymphoma, prognostication, and assessment of treatment response, they still face significant challenges. Over the past few years, radiomics and artificial intelligence (AI) have surfaced as valuable tools for detecting subtle features within medical images that may not be easily discerned by visual assessment. The rapid expansion of AI and its application in medicine/radiomics is opening up new opportunities in the nuclear medicine field. Radiomics and AI capabilities seem to hold promise across various clinical scenarios related to lymphoma. Nevertheless, the need for more extensive prospective trials is evident to substantiate their reliability and standardize their applications. This review aims to provide a comprehensive perspective on the current literature regarding the application of AI and radiomics applied/extracted on/from 18F-FDG PET/CT in the management of lymphoma patients.

Prospects and challenges of neoantigen applications in oncology.

Neoantigen, unique peptides resulting from tumor-specific mutations, represent a promising frontier in oncology for personalized cancer immunotherapy. Their unique features allow for the development of highly specific and effective cancer treatments, which can potentially overcome the limitations of conventional therapies. This paper explores the current prospects and challenges associated with the application of neoantigens in oncology. We examine the latest advances in neoantigen identification, vaccine development, and adoptive T cell therapy. Additionally, we discuss the obstacles related to neoantigen heterogeneity, immunogenicity prediction, and the tumor microenvironment. Through a comprehensive analysis of current research and clinical trials, this paper aims to provide a detailed overview of how neoantigens could revolutionize cancer treatment and the hurdles that must be overcome to realize their full potential.

My virtual escape from patient life: a feasibility study on the experiences and benefits of individualized virtual reality for inpatients in palliative cancer care.

BACKGROUND: Cancer patients benefit from Virtual Reality (VR) in burdensome situations, but evidence is scarce for palliative situations. Based on earlier work in palliative care, individualized VR interventions like seeing the patient's home may address a patient's wish to be at home and thus have a greater effect compared to standard VR content. Yet, some patients and relatives may be concerned about their privacy. Also, patient stakeholders raised concerns about triggering depressed mood or homesickness. AIM: To test the feasibility and safety of individualized vs. standard 360°video VR interventions in palliative cancer inpatients. METHODS: Prospective observational study with patient-reported outcome measurement using validated instruments of well-being (MDBF), symptoms and psychosocial burden (IPOS), cybersickness (SSQ), presence experience (SPES), subjective benefit (2 items), content analysis of interviews, and field notes. Individualized VR content was recorded with action camcorder-technology to protect the patients' privacy. RESULTS: Seventeen patients participated, median age 65 years (range 20-82), 9 women (53%), 8 single or widowed (47%), 4 childless (23.5%), 4 academics (23.5%), with a median length of stay of 9 days (1-75) in the hematology (10), palliative care (3), or radiotherapy (2) unit of a German university hospital. Eight patients (53.3%) chose their own home environments or family for individualized VR-content. All participants enjoyed the intervention. Compared to standard VR content the individualized VR tended to have a stronger effect on well-being and emotional touch. It was not inferior in terms of psychosocial burden and cybersickness. No subjective and relevant side effects occurred. The patients well tolerated the assessments. However, most patients demanded a lighter headset and a desire for more interactivity. CONCLUSIONS: Individualization of VR content shows potential for enhancement of immersion, which improves the VR experience and does not harm in terms of depressed mood or worsening of symptoms. The patients' and family desire for privacy is feasible with the support of family members who recorded the individualized videos, which is easily manageable today. We suggest a pragmatic randomized clinical trial to compare the effects of individualized vs. standard VR-content. TRIAL REGISTRATION: Registered at German Clinical Trials Register (Deutsches Register Klinischer Studien; DRKS); registration number: DRKS00032172; registration date: 11/07/2023.

Tailored management of advanced thyroid cancer patients treated with lenvatinib or vandetanib: the role of a multimodal approach.

BACKGROUND: In differentiated/poorly differentiated (DTC/PDTC) or medullary thyroid cancer (MTC) treated with kinase inhibitors (KIs), additional treatments (ATs) can be performed in selected cases. METHODS: We retrospectively analysed all the ATs performed in our center in KI-treated TC patients, evaluating the subsequent KI modulation, the local PD in case of loco-regional procedure (LRP) and the AT-related complications. DTC/PDTC patients with or without progressive disease before the first AT (PD and NO PD GROUP, respectively) were analysed separately. RESULTS: In our center, 32 ATs (30 LRPs and 2 radioactive iodine treatments) were performed in 14 DTC/PDTC patients and 4 MTC subjects after the start of systemic therapy with lenvatinib or vandetanib (27 and 5 ATs, respectively). Brain was the most treated site (11/30 LRPs) and external beam radiation was the most employed LRP (18/30 LRPs). KIs dose reduction or discontinuation of KI therapy (at least transient) was performed after 50% of ATs in DTC/PDTC NO PD GROUP. The KI was maintained at the same dosage after 75% and 50% of the ATs performed in DTC/PDTC PD GROUP and MTC, respectively. During the follow-up, local PD was detected after 14 LRPs. Local progression-free survival (LPFS) was significantly shorter in DTC/PDTC PD GROUP in comparison to NO PD GROUP (12 month-LPFS 91.7% versus 15.2%); in patients with MTC, 12 month-LPFS was 50%. AT-related AEs were mostly G1-G2. CONCLUSIONS: In selected DTC/PDTC without previous PD and treated with a multimodal strategy, local disease control is generally maintained regardless the KI dose modulation. In DTC/PDTC patients with previous limited PD and in MTC subjects, the choice of performing a LRP and continue the ongoing KI therapy must consider the risk of early local progression. AT-related AEs in KI treated patients were mild in most cases.

Disruptions in antigen processing and presentation machinery on sarcoma.

BACKGROUND: The antigen processing machinery (APM) plays a critical role in generating tumor-specific antigens that can be recognized and targeted by the immune system. Proper functioning of APM components is essential for presenting these antigens on the surface of tumor cells, enabling immune detection and destruction. In many cancers, defects in APM can lead to immune evasion, contributing to tumor progression and poor clinical outcomes. However, the status of the APM in sarcomas is not well characterized, limiting the development of effective immunotherapeutic strategies for these patients. METHODS: We investigated 126 patients with 8 types of bone and soft tissue sarcoma operated between 2001-2021. Tissue microarrays mapped 11 specific areas in each case. The presence/absence of APM protein was determined through immunohistochemistry. Bayesian networks were used. RESULTS: All investigated sarcomas had some defects in APM. The least damaged component was HLA Class I subunit ß2-microglobulin and HLA Class II. The proteasome LMP10 subunit was defective in leiomyosarcoma (LMS), myxoid liposarcoma (MLPS), and dedifferentiated liposarcoma (DDLPS), while MHC I transporting unit TAP2 was altered in undifferentiated pleomorphic sarcoma (UPS), gastrointestinal stromal tumor (GIST), and chordoma (CH). Among different neoplastic areas, high-grade areas showed different patterns of expression compared to high lymphocytic infiltrate areas. Heterogeneity at the patient level was also observed. Loss of any APM component was prognostic of distant metastasis (DM) for LMS and DDLPS and of overall survival (OS) for LMS. CONCLUSION: Sarcomas exhibit a high degree of defects in APM components, with differences among histotypes and tumoral areas. The most commonly altered APM components were HLA Class I subunit ß2-microglobulin, HLA Class I subunit α (HC10), and MHC I transporting unit TAP2. The loss of APM components was prognostic of DM and OS and clinically relevant for LMS and DDLPS. This study explores sarcoma molecular mechanisms, enriching personalized therapeutic approaches.

Polθ Inhibitor (ART558) Demonstrates a Synthetic Lethal Effect with PARP and RAD52 Inhibitors in Glioblastoma Cells.

DNA repair proteins became the popular targets in research on cancer treatment. In our studies we hypothesized that inhibition of DNA polymerase theta (Polθ) and its combination with Poly (ADP-ribose) polymerase 1 (PARP1) or RAD52 inhibition and the alkylating drug temozolomide (TMZ) has an anticancer effect on glioblastoma cells (GBM21), whereas it has a low impact on normal human astrocytes (NHA). The effect of the compounds was assessed by analysis of cell viability, apoptosis, proliferation, DNA damage and cell cycle distribution, as well as gene expression. The main results show that Polθ inhibition causes a significant decrease in glioblastoma cell viability. It induces apoptosis, which is accompanied by a reduction in cell proliferation and DNA damage. Moreover, the effect was stronger when dual inhibition of Polθ with PARP1 or RAD52 was applied, and it is further enhanced by addition of TMZ. The impact on normal cells is much lower, especially when considering cell viability and DNA damage. In conclusion, we would like to highlight that Polθ inhibition used in combination with PARP1 or RAD52 inhibition has great potential to kill glioblastoma cells, and shows a synthetic lethal effect, while sparing normal astrocytes.

Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies.

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program's strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers.

The Pivotal Role of Preclinical Animal Models in Anti-Cancer Drug Discovery and Personalized Cancer Therapy Strategies.

The establishment and utilization of preclinical animal models constitute a pivotal aspect across all facets of cancer research, indispensably contributing to the comprehension of disease initiation and progression mechanisms, as well as facilitating the development of innovative anti-cancer therapeutic approaches. These models have emerged as crucial bridges between basic and clinical research, offering multifaceted support to clinical investigations. This study initially focuses on the importance and benefits of establishing preclinical animal models, discussing the different types of preclinical animal models and recent advancements in cancer research. It then delves into cancer treatment, studying the characteristics of different stages of tumor development and the development of anti-cancer drugs. By integrating tumor hallmarks and preclinical research, we elaborate on the path of anti-cancer drug development and provide guidance on personalized cancer therapy strategies, including synthetic lethality approaches and novel drugs widely adopted in the field. Ultimately, we summarize a strategic framework for selecting preclinical safety experiments, tailored to experimental modalities and preclinical animal species, and present an outlook on the prospects and challenges associated with preclinical animal models. These models undoubtedly offer new avenues for cancer research, encompassing drug development and personalized anti-cancer protocols. Nevertheless, the road ahead continues to be lengthy and fraught with obstacles. Hence, we encourage researchers to persist in harnessing advanced technologies to refine preclinical animal models, thereby empowering these emerging paradigms to positively impact cancer patient outcomes.

Systematic assessment of HER2 status in ductal carcinoma in situ of the breast: a perspective on the potential clinical relevance.

In many countries, hormone receptor status assessment of ductal carcinoma in situ (DCIS) is routinely performed, as hormone receptor-positive DCIS patients are eligible for adjuvant anti-hormonal treatment, aiming to reduce the ipsilateral and contralateral breast cancer risk. Although HER2 gene amplification and its associated HER2 protein overexpression constitute a major prognostic and predictive marker in invasive breast carcinoma, its use in the diagnosis and treatment of DCIS is less straightforward. HER2 immunohistochemistry is not routinely performed yet, as the role of HER2-positivity in DCIS biology is unclear. Nonetheless, recent data challenge this practice. Here, we discuss the value of routine HER2 assessment for DCIS. HER2-positivity correlates strongly with DCIS grade: around four in five HER2-positive DCIS show high grade atypia. As morphological DCIS grading is prone to interobserver variability, HER2 immunohistochemistry could render grading more robust. Several studies showed an association between HER2-positive DCIS and ipsilateral recurrence risk, albeit currently unclear whether this is for overall, in situ or invasive recurrence. HER2-positive DCIS tends to be larger, with a higher risk of involved surgical margins. HER2-positive DCIS patients benefit more from adjuvant radiotherapy: it substantially decreases the local recurrence risk after lumpectomy, without impact on overall survival. HER2-positivity in pure biopsy-diagnosed DCIS is associated with increased upstaging to invasive carcinoma after surgery. HER2 immunohistochemistry on preoperative biopsies might therefore provide useful information to surgeons, favoring wider excisions. The time seems right to consider DCIS subtype-dependent treatment, comprising appropriate local treatment for HER2-positive DCIS patients and de-escalation for hormone receptor-positive, HER2-negative DCIS patients.

Update on the PriME-PGx initiative: evolution of pharmacogenetics in daily clinical practice.

In 2021, the Clinical Pharmacology Department of Hospital Universitario de La Princesa launched the PriME-PGx initiative (Multidisciplinary Initiative of the Hospital Universitario de La Princesa for the Implementation of Pharmacogenetics) to promote the expansion of pharmacogenetics in hospitalized patients. We establish seven pharmacogenetic profiles based on the specific needs of seven departments: Oncology, Pain Unit, Neuropsychiatry, Internal or Infectious Medicine, Cardiology, Gastroenterology and Immunosuppressants. The experience of the last 3 years reflects a total of 1421 reports (37.4% being oncology profiles), with a gradual increase in the number of requests each year. With this project, we aim to expand the availability and utility of pharmacogenetic biomarkers to achieve personalised therapy that avoids adverse drug reactions and therapeutic failure.

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Optimizing cancer patient care with a robust assay for 5-fluorouracil quantification and in-vitro stability in human blood for therapeutic drug monitoring.

Background: The plasma concentration of 5-Fluorouracil (5-FU) is affected by numerous factors, thereby limiting its efficacy. The current therapeutic regimen's doses based on body surface area (BSA) are linked to increased toxicity and sometimes inadequate drug exposure. Aim and objectives: The study aims to develop an in-vitro assay to monitor 5-Fluorouracil's therapeutic efficacy in cancer patients' blood samples, focusing on pharmacokinetics to improve therapy precision. Materials and methods: Drug levels were determined from standards, quality controls, and experimental samples using protein precipitation, liquid-liquid extraction, and separation using a C18 analytical column with an isocratic program. Result: In EXP-1A, the mean concentration of 5-Fluorouracil was 1.15 µg/ml; in EXP-1B, it was 1.16 µg/ml, while in EXP-1C, the mean concentration was 0.9 µg/ml. The percentage difference in mean 5-Fluorouracil concentration between the experiment sample containing a DPD inactivator and EXP-1C (without a DPD inactivator) was 21.5 % higher for EXP-1A and 0.68 % higher for EXP-1B. In the second phase of the experiment, the overall stability of 5-Fluorouracil in samples containing a DPD inactivator was 24.5 % superior compared to samples without a DPD inactivator. Conclusion: A modified extraction technique has been developed to accurately measure 5-Flourouracil concentration in blood, preserving its stability and concentration by adding a DPD inactivator.

Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies.

Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different types of cancers. However, the current approaches to RPTs often follow a somewhat inflexible "one size fits all" paradigm, where patients are administered the same amount of radioactivity per cycle regardless of their individual characteristics and features. This approach fails to consider inter-patient variations in radiopharmacokinetics, radiation biology, and immunological factors, which can significantly impact treatment outcomes. To address this limitation, we propose the development of theranostic digital twins (TDTs) to personalize RPTs based on actual patient data. Our proposed roadmap outlines the steps needed to create and refine TDTs that can optimize radiation dose to tumors while minimizing toxicity to organs at risk. The TDT models incorporate physiologically-based radiopharmacokinetic (PBRPK) models, which are additionally linked to a radiobiological optimizer and an immunological modulator, taking into account factors that influence RPT response. By using TDT models, we envisage the ability to perform virtual clinical trials, selecting therapies towards improved treatment outcomes while minimizing risks associated with secondary effects. This framework could empower practitioners to ultimately develop tailored RPT solutions for subgroups and individual patients, thus improving the precision, accuracy, and efficacy of treatments while minimizing risks to patients. By incorporating TDT models into RPTs, we can pave the way for a new era of precision medicine in cancer treatment.

Occurrence of Secondary Non-Hodgkin Lymphomas Among Our Classical Hodgkin Lymphoma Patients: A Single-Centre Experience.

Objective Non-Hodgkin lymphoma (NHL) arising as a secondary malignancy in patients treated for classical Hodgkin lymphoma (cHL) is an infrequent and challenging clinical scenario. NHL can be presented synchronously with cHL or may develop later, sequentially, up to years after treatment for cHL. The relationship between the two lymphomas is unclear, and there are no clear guidelines for the management of these patients. We would like to find a better clinical understanding of this issue so this study investigates the occurrence and clinical characteristics of secondary NHL. Materials and methods In this retrospective cohort examination, we collected cHL cases when NHL occurred during or after the course of treating cHL. We performed the histopathologic revisions of the samples, and in every case where the quality of the sample was lower, we performed molecular examinations to find the association between cHL and NHL. We performed next-generation genome sequencing (NGS) and immunoglobulin heavy-chain variable region gene (IgHV) clonality testing. Results In a cohort of 164 cHL patients diagnosed between 2011 and 2020, six patients were identified with NHL during rebiopsy prompted by lymphoma relapse or progression. Among these, five patients were diagnosed with post-germinal center-originated diffuse large B-cell lymphoma (post-GC DLBCL), and one patient presented high-grade B-cell lymphoma (HG-BCL). The NHL manifestation differed in its timing: three cases emerged after successful cHL treatment, with at least 18 months of complete remission, while the other three patients faced primary refractory cHL. Notably, the primary refractory cases did not exhibit a confirmed clonal relationship between cHL and NHL, but NGS data raised the possibility of synchronous NHL in one case. In contrast, among the patients with sequentially occurring NHL, polymerase chain reaction (PCR) testing of the IgHV gene affirmed a clonal connection between cHL and secondary DLBCL in one case, while the high morphological similarity suggested a potential clonality between the two lymphomas in another case. Conclusion This study reveals that secondary NHL may manifest both synchronously and sequentially following cHL. Our results suggest that synchronous NHL has a worse prognosis compared to sequential cases when the different lymphomas are not recognized at the time of diagnosis. As our data showed, in some cases, mutations that accompany the tumor cells throughout their clonal evolution can be identified, with additional mutations later on. In the future, next-generation sequencing (NGS)-based processing of liquid biopsy samples can overcome the limitations resulting from the spatial heterogeneity of lymphoid malignancies. Over the long term, this identification could lead to early patient selection and alternative treatment strategies, ultimately leading to improved prospects for cure.

Differences in Clinicopathological Features, P16Ink4a and P57KIP2 Immunohistochemical Expressions, and Survival Between Colorectal Carcinoma in Rectosigmoid and Other Colonic Locations.

Background One unique criterion of colorectal carcinoma (CRC) is the different locations within the colorectum. Different CRC sidedness/locations could have distinct criteria, including risk factors, morphological features, genetic alterations, prognostic factors, and clinical outcomes. Nearly half of the CRC cases occur in the rectal-sigmoid locations, while other colonic locations constitute the other half. Investigating specific protein expression patterns in the rectosigmoid CRC (rsCRC) compared to other colonic (ocCRC) locations helps understand the disease pathogenesis, predict prognosis, and design personalized treatments. This study is the first to compare P16Ink4a and P57KIP2 immunohistochemical (IHC) expression in rsCRC to ocCRC and examine their relationship to disease outcomes in both locations. Materials and methods A comparative cross-sectional study used tissue microarray slides from rsCRC and ocCRC that were immunohistochemically stained by anti-P16Ink4a and P57KIP2 antibodies. A semi-quantitative scoring system classified each marker's expression as positive or negative. The statistical analysis compared clinicopathological features, P16Ink4a and P57KIP2 expressions, and their relationship to clinical outcomes in rsCRC and ocCRC cases. Results One hundred fifty CRCs were distributed into the rsCRC cases (n=86, 57.3%) and the ocCRC cases (n=64, 42.7%). The rsCRC cases had a significantly lower age <40 years (P=0.002), higher frequency of mismatch repair (MMR) proficient status (P=0.003), and perineural invasion (P=0.008), with lower disease-free (DFS) and overall survival (OS) (P=0.03, and P=0.015, respectively). Significantly higher positive P16Ink4a and P57KIP2 IHC expressions were found in the rsCRCs compared to the ocCRCs (P=0.02, and P=0.03, respectively); however, their relationship to the hazards (HR) of recurrence (HR=4.02, P=0.058, and HR=0.36, P=0.14, respectively) and mortality (HR=2.56, P=0.21, and HR=0.23, P=0.58, respectively) in the rsCRC group was statistically nonsignificant. In the ocCRC group, P16Ink4a positivity was significantly associated with a higher disease recurrence and mortality hazard (HR=8.19, P=0.007, and HR=5.57, P=0.037, respectively), while P57KIP2 positivity was significantly associated with a lower mortality hazard (HR=0.12, P=0.027). Conclusion The rsCRCs differ from ocCRCs in clinicopathological criteria and protein expression patterns. Though P16Ink4a and P57KIP2 IHC expressions are higher in the rsCRC than in the ocCRC, their value as outcome predictors is higher in the ocCRCs rather than the rsCRCs. P16Ink4a and P57KIP2 can act as prognostic markers and be suitable targets for therapy modulation in the ocCRC group.