Chemotherapy outcome predictive effectiveness by the Oncogramme: pilot trial on stage-IV colorectal cancer

The New Frontiers of Gene Therapy and Gene Editing in Inflammatory Diseases

Inflammatory diseases are conditions characterized by abnormal and often excessive immune responses, leading to tissue and organ inflammation. The complexity of these disorders arises from the intricate interplay of genetic factors and immune responses, which challenges conventional therapeutic approaches. However, the field of genetic manipulation has sparked unprecedented optimism in addressing these complex disorders. This review aims to comprehensively explore the application of gene therapy and gene editing in the context of inflammatory diseases, offering solutions that range from correcting genetic defects to precise immune modulation. These therapies have exhibited remarkable potential in ameliorating symptoms, improving quality of life, and even achieving disease remission. As we delve into recent breakthroughs and therapeutic applications, we illustrate how these advancements offer novel and transformative solutions for conditions that have traditionally eluded conventional treatments. By examining successful case studies and preclinical research, we emphasize the favorable results and substantial transformative impacts that gene-based interventions have demonstrated in patients and animal models of inflammatory diseases such as chronic granulomatous disease, cryopyrin-associated syndromes, and adenosine deaminase 2 deficiency, as well as those of multifactorial origins such as arthropathies (osteoarthritis, rheumatoid arthritis) and inflammatory bowel disease. In conclusion, gene therapy and gene editing offer transformative opportunities to address the underlying causes of inflammatory diseases, ushering in a new era of precision medicine and providing hope for personalized, targeted treatments.

Functional Drug Screening in the Era of Precision Medicine

The focus of precision medicine is providing the right treatment to each unique patient. This scientific movement has incited monumental advances in oncology including the approval of effective, targeted agnostic therapies. Yet, precision oncology has focused largely on genomics in the treatment decision making process, and several recent clinical trials demonstrate that genomics is not the only variable to be considered. Drug screening in three dimensional (3D) models, including patient derived organoids, organs on a chip, xenografts, and 3D-bioprinted models provide a functional medicine perspective and necessary complement to genomic testing. In this review, we discuss the practicality of various 3D drug screening models and each model's ability to capture the patient's tumor microenvironment. We highlight the potential for enhancing precision medicine that personalized functional drug testing holds in combination with genomic testing and emerging mathematical models.

Benefits of functional assays in personalized cancer medicine: more than just a proof-of-concept

As complex and heterogeneous diseases, cancers require a more tailored therapeutic management than most pathologies. Recent advances in anticancer drug development, including the immuno-oncology revolution, have been too often plagued by unsatisfying patient response rates and survivals. In reaction to this, cancer care has fully transitioned to the “personalized medicine” concept. Numerous tools are now available tools to better adapt treatments to the profile of each patient. They encompass a large array of diagnostic assays, based on biomarkers relevant to targetable molecular pathways. As a subfamily of such so-called companion diagnostics, chemosensitivity and resistance assays represent an attractive, yet insufficiently understood, approach to individualize treatments. They rely on the assessment of a composite biomarker, the ex vivo functional response of cancer cells to drugs, to predict a patient's outcome. Systemic treatments, such as chemotherapies, as well as targeted treatments, whose efficacy cannot be fully predicted yet by other diagnostic tests, may be assessed through these means. The results can provide helpful information to assist clinicians in their decision-making process. We explore here the most advanced functional assays across oncology indications, with an emphasis on tests already displaying a convincing clinical demonstration. We then recapitulate the main technical obstacles faced by researchers and clinicians to produce more accurate, and thus more predictive, models and the recent advances that have been developed to circumvent them. Finally, we summarize the regulatory and quality frameworks surrounding functional assays to ensure their safe and performant clinical implementation. Functional assays are valuable in vitro diagnostic tools that already stand beyond the “proof-of-concept” stage. Clinical studies show they have a major role to play by themselves but also in conjunction with molecular diagnostics. They now need a final lift to fully integrate the common armament used against cancers, and thus make their way into the clinical routine.

ONCOGRAM: study protocol for the evaluation of therapeutic response and survival of metastatic colorectal cancer patients treated according to the guidelines of a chemosensitivity assay, the Oncogramme®

Background

Colorectal cancer is a major public concern, being the second deadliest cancer in the world. Whereas survival is high for localized forms, metastatic colorectal cancer has showed poor prognosis, with a 5-year survival barely surpassing 11%. Conventional chemotherapies against this disease proved their efficiency and remain essential in first-line treatment. However, the large number of authorized protocols complexifies treatment decision. In common practice, such decision is made on an empirical basis, by assessing benefits and risks for the patient. In other words, there is currently no efficient means of predicting the efficacy of any chemotherapy protocol for metastatic colorectal cancer.

Methods/design

The use of a chemosensitivity assay, the Oncogramme®, should help clinicians administer the best chemotherapy regimen to their patients. We hypothesize it would ultimately improve their survival. In this multicentred, prospective trial (ONCOGRAM), eligible patients with metastatic colorectal cancer are randomized to determine whether they will receive an Oncogramme®. For clinicians whose patients benefited from the assay (arm A), results are used as a decision support tool. Patients not undergoing the Oncogramme® procedure are treated according to current practice, without the assistance of the assay (arm B). Primary outcome is 1-year progression-free survival. Secondary outcomes include response rates, as well as 6-month and 1-year survival rates.

Discussion

This study aims at investigating the clinical utility of the Oncogramme® as a decision support tool for the treatment of patients with metastatic colorectal cancer. If the Oncogramme® positively influenced patient overall survival and/or progression-free survival, it would be of great value for clinicians to implement this assay within the current landscape of personalized medicine tools, which include genomics and biomarker assays.

Trial registration

ClinicalTrials.gov identifier NCT03133273. Registered on April 28, 2017.

Patient-Derived Colorectal Cancer Organoids Upregulate Revival Stem Cell Marker Genes following Chemotherapeutic Treatment

Colorectal cancer stem cells have been proposed to drive disease progression, tumour recurrence and chemoresistance. However, studies ablating leucine rich repeat containing G protein-coupled receptor 5 (LGR5)-positive stem cells have shown that they are rapidly replenished in primary tumours. Following injury in normal tissue, LGR5+ stem cells are replaced by a newly defined, transient population of revival stem cells. We investigated whether markers of the revival stem cell population are present in colorectal tumours and how this signature relates to chemoresistance. We examined the expression of different stem cell markers in a cohort of patient-derived colorectal cancer organoids and correlated expression with sensitivity to 5-fluorouracil (5-FU) treatment. Our findings revealed that there was inter-tumour variability in the expression of stem cell markers. Clusterin (CLU), a marker of the revival stem cell population, was significantly enriched following 5-FU treatment and expression correlated with the level of drug resistance. Patient outcome data revealed that CLU expression is associated with both lower patient survival and an increase in disease recurrence. This suggests that CLU is a marker of drug resistance and may identify cells that drive colorectal cancer progression.

Inventory of oncologists' unmet needs for tools to support decision-making about palliative treatment for metastatic colorectal cancer

BACKGROUND

Decision-making about palliative care for metastatic colorectal cancer (mCRC) consists of many different treatment-related decisions, and there generally is no best treatment option. Decision support systems (DSS), e.g., prognostic calculators, can aid oncologists' decision-making. DSS that contain features tailored to the needs of oncologists are more likely to be implemented in clinical practice. Therefore, our aim is to inventory colorectal cancer specialists' unmet decision support needs.

METHODS

We asked oncologists from the Dutch colorectal cancer group (DCCG), to participate in an online inventory questionnaire on their unmet decision support needs. To get more in-depth insight in required features of the DSS they need, we also conducted semi-structured telephone interviews.

RESULTS

Forty-one oncologists started the inventory questionnaire, and 27 of them completed all items. Of all respondents, 18 were surgeons (44%), 22 were medical oncologists (54%), and 28 (68%) had more than 10 years of experience treating mCRC. In both the inventory questionnaire and interviews, respondents expressed a need for an overarching DSS incorporating multiple treatment options, and presenting both the treatment benefits and harms. Respondents found it relevant for other outcomes, such as cost-effectiveness of treatment or quality of life, to be incorporated in DSS. There was also a wish for DSS incorporating an up-to-date "personalized" overview of the ongoing trials for which a specific patient is eligible.

CONCLUSIONS

Experienced oncologists indicate that their treatment advice is currently almost solely based on the available clinical guidelines. They experience a lack of good quality DSS to help them personalize their treatment advice. New tools integrating multiple treatment options and providing a broad range of clinically relevant outcomes are urgently needed to stimulate and safeguard more personalized treatment decision-making.

Bringing 3D tumor models to the clinic - predictive value for personalized medicine

Current decision-guiding algorithms in cancer drug treatment are based on decades of research and numerous clinical trials. For the majority of patients, this data is successfully applied for a systemic disease management. For a number of patients however, treatment stratification according to clinically based risk criteria will not be sufficient. The most effective treatment options are ideally identified prior to the start of clinical drug therapy. This review will discuss the implementation of three-dimensional (3D) cell culture models as a preclinical testing paradigm for the efficacy of clinical cancer treatment. Patient tumor-derived cells in 3D cultures duplicate the individual tumor microenvironment with a minimum of confounding factors. Clinical implementation of such personalized tumor models requires a high quality of methodological and clinical validation comparable to other biomarkers. A non-systematic literature search demonstrated the small number of prospective studies that have been conducted in this area of research. This may explain the current reluctance of many physicians and insurance providers in implementing this type of assay into the clinical diagnostic routine despite potential benefit for patients. Achieving valid and reproducible results with a high level of evidence is central in improving the acceptance of preclinical 3D tumor models.

UGT1A1 gene polymorphism is associated with toxicity and clinical efficacy of irinotecan-based chemotherapy in patients with advanced colorectal cancer

OBJECTIVES

To investigate the relationship between uridine diphosphate glucoronosyltransferase 1A1 (UGT1A1)*28/*6 and toxicity and clinical efficacy of irinotecan-based chemotherapy in patients with advanced colorectal cancer (CRC) in Xinjiang Uygur and Han population.

METHODS

A total of 183 patients (Uygur, 114; Han, 69) with advanced CRC who received the irinotecan-based chemotherapy were enrolled in this retrospective analysis. Polymerase chain reaction amplification and direct sequencing method were used for UGT1A1*28 and UGT1A1*6 polymorphism detection. The patients were followed up to analyze the relationship between different genotypes with adverse reactions and the clinical outcome of irinotecan-based chemotherapy.

RESULTS

Significant differences were found in genotype frequencies of UGT1A1*28 and UGT1A1*28/*6 between Uygur and Han (P = 0.02 and P = 0.002). Uygur and Han patients carrying wild UGT1A1*28 and *6 genotypes appeared to have significantly lower diarrhea incidence (I/II and III/IV) than those carrying mutant genotypes (all P < 0.05). In Uygur patients, UGT1A1*28 genotypes were related with objective response rate and disease control rate (P < 0.05). Compared with *1 allele *1/*1, *1 allele *1/*28*1/*28 mutant of UGT1A1*28 was associated with shorter OS in both Uygur and Han ethnicities (all P < 0.05). Compared with double allele variants (DW), single allele variants (SV), and double allele variants (DV) of UGT1A1*28/*6 were associated with shorter overall survival (OS) in Uygur and Han (all P < 0.05). Cox regression analysis revealed factors significantly influencing OS, including UGT1A1*28, UGT1A1*6, combined genotypes and chemotherapy line in Ugyur, and only combined genotypes in Han (all P < 0.05).

CONCLUSION

UGT1A1 gene polymorphism predicts irinotecan-related adverse reactions in advanced CRC patients of Xinjiang Uygur and Han nationality; UGT1A1 gene polymorphism is correlated with efficacy and prognosis in Uygur nationality, but only related to prognosis in Han nationality in irinotecan-based chemotherapy.