Defining Survivorship Trajectories Across Patients With Solid Tumors

Dood, Robert; Zhao, Yang; Armbruster, Shannon D.; Coleman, Robert L.; Tworoger, Shelley S.; Sood, Anil K.; Baggerly, Keith A.

doi:10.1001/jamaoncol.2018.2761

Cited by 49 publications

(37 citation statements)

References 14 publications

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“…Despite initial therapy, the disease recurs in about 70–80% of advanced-stage patients, and the 10 year disease-free survival rate is below 15% in these patients (Coleman et al 2019 ; Dood et al 2018 ). If the disease recurs 12 months or later after the end of platinum therapy, the tumor is “platinum sensitive”, in a range between 6 and 12 months the tumor is “partially platinum sensitive”, and recurrence within 6 months means “platinum resistant” disease.…”

Section: Etiology and Treatment Of Ovarian Cancermentioning

confidence: 99%

The role of the microbiome in ovarian cancer: mechanistic insights into oncobiosis and to bacterial metabolite signaling

Sipos

Ujlaki

Mikó

et al. 2021

Mol Med

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Ovarian cancer is characterized by dysbiosis, referred to as oncobiosis in neoplastic diseases. In ovarian cancer, oncobiosis was identified in numerous compartments, including the tumor tissue itself, the upper and lower female genital tract, serum, peritoneum, and the intestines. Colonization was linked to Gram-negative bacteria with high inflammatory potential. Local inflammation probably participates in the initiation and continuation of carcinogenesis. Furthermore, local bacterial colonies in the peritoneum may facilitate metastasis formation in ovarian cancer. Vaginal infections (e.g. Neisseria gonorrhoeae or Chlamydia trachomatis) increase the risk of developing ovarian cancer. Bacterial metabolites, produced by the healthy eubiome or the oncobiome, may exert autocrine, paracrine, and hormone-like effects, as was evidenced in breast cancer or pancreas adenocarcinoma. We discuss the possible involvement of lipopolysaccharides, lysophosphatides and tryptophan metabolites, as well as, short-chain fatty acids, secondary bile acids and polyamines in the carcinogenesis of ovarian cancer. We discuss the applicability of nutrients, antibiotics, and probiotics to harness the microbiome and support ovarian cancer therapy. The oncobiome and the most likely bacterial metabolites play vital roles in mediating the effectiveness of chemotherapy. Finally, we discuss the potential of oncobiotic changes as biomarkers for the diagnosis of ovarian cancer and microbial metabolites as possible adjuvant agents in therapy.

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Section: Etiology and Treatment Of Ovarian Cancermentioning

confidence: 99%

The role of the microbiome in ovarian cancer: mechanistic insights into oncobiosis and to bacterial metabolite signaling

Sipos

Ujlaki

Mikó

et al. 2021

Mol Med

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“…The integration of multidimensional data necessitates new analytic and bioinformatics methods, such as machine learning, which has resulted in novel risk stratification in patients with heart failure, as well as within the survivorship setting. As an initial step, Dood et al applied hierarchical clustering analyses to overall survival data from a total of 2317,185 patients (median age, 63 years; 49.8% female) with 66 primary tumor types and identified 6 risk cluster groups that significantly differed in medial survival and mortality gap compared with the general population (eg, a “low‐risk” cluster had a median survival of 16.2 years and a 1.4% mortality gap; a “high‐risk” cluster had a median survival of 1.6 years and a 6.1% mortality gap). Importantly, their study defined survivorship clusters based on patient‐level factors, such as stage and histologic subtype, rather than tumor location (eg, breast, prostate) and distinguished clusters that would benefit from oncology‐lead care or early PCP‐led care within the first 5 years after treatment cessation.…”

Section: Developing a Blueprint For Implementation In The United Statesmentioning

confidence: 99%

Implementing personalized pathways for cancer follow‐up care in the United States: Proceedings from an American Cancer Society–American Society of Clinical Oncology summit

Alfano

Mayer

Bhatia

et al. 2019

CA A Cancer J Clinicians

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A new approach to cancer follow‐up care is necessary to meet the needs of cancer survivors while dealing with increasing volume and provider shortages, knowledge gaps, and costs to both health care systems and patients. An approach that triages patients to personalized follow‐up care pathways, depending on the type(s) and level(s) of resources needed for patients’ long‐term care, is in use in the United Kingdom and other countries and has been shown to meet patients’ needs, more efficiently use the health care system, and reduce costs. Recognizing that testing and implementing a similar personalized approach to cancer follow‐up care in the United States will require a multipronged strategy, the American Cancer Society and the American Society of Clinical Oncology convened a summit in January 2018 to identify the needed steps to move this work from concept to implementation. The summit identified 4 key strategies going forward: 1) developing a candidate model (or models) of care delivery; 2) building the case for implementation by conducting studies modeling the effects of personalized pathways of follow‐up care on patient outcomes, workforce and health care resources, and utilization and costs; 3) creating consensus‐based guidelines to guide the delivery of personalized care pathways; and 4) identifying and filling research gaps to develop and implement needed care changes. While these national strategies are pursued, oncology and primary care providers can lay the groundwork for implementation by assessing their patients’ risk of recurrence and the chronic and late effects of cancer as well as other health care needs and resources available for care and by considering triaging patients accordingly, referring patients to appropriate specialized survivorship clinics as these are developed, helping to support patients who are capable of self‐managing their health, setting expectations with patients from diagnosis onward for the need for follow‐up in primary care and/or a survivorship clinic, and improving coordination of care between oncology and primary care.

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“…Cytoreductive surgery and platinum-and paclitaxel-based chemotherapy are still the basic treatments for OC. Despite advances in combination chemotherapy, targeted therapy and intraperitoneal chemotherapy, 80% of OC patients initially respond to treatment, but most eventually relapse and ultimately develop into a chemotherapy-resistant disease; thus, no significant improvement in the prognosis of OC has been achieved (2)(3)(4).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Autophagy-Related Signatures Identified Two Distinct Subtypes for Evaluating the Tumor Immune Microenvironment and Predicting Prognosis in Ovarian Cancer

Chen

Lan

et al. 2021

Front. Oncol.

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Ovarian cancer (OC) is one of the most lethal gynecologic malignant tumors. The interaction between autophagy and the tumor immune microenvironment has clinical importance. Hence, it is necessary to explore reliable biomarkers associated with autophagy-related genes (ARGs) for risk stratification in OC. Here, we obtained ARGs from the MSigDB database and downloaded the expression profile of OC from TCGA database. The k-means unsupervised clustering method was used for clustering, and two subclasses of OC (cluster A and cluster B) were identified. SsGSEA method was used to quantify the levels of infiltration of 24 subtypes of immune cells. Metascape and GSEA were performed to reveal the differential gene enrichment in signaling pathways and cellular processes of the subtypes. We found that patients in cluster A were significantly associated with higher immune infiltration and immune-associated signaling pathways. Then, we established a risk model by LASSO Cox regression. ROC analysis and Kaplan-Meier analysis were applied for evaluating the efficiency of the risk signature, patients with low-risk got better outcomes than those with high-risk in overall survival. Finally, ULK2 and GABARAPL1 expression was further validated in clinical samples. In conclusion, Our study constructed an autophagy-related prognostic indicator, and identified two promising targets in OC.

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Defining Survivorship Trajectories Across Patients With Solid Tumors

Cited by 49 publications

References 14 publications

The role of the microbiome in ovarian cancer: mechanistic insights into oncobiosis and to bacterial metabolite signaling

The role of the microbiome in ovarian cancer: mechanistic insights into oncobiosis and to bacterial metabolite signaling

Implementing personalized pathways for cancer follow‐up care in the United States: Proceedings from an American Cancer Society–American Society of Clinical Oncology summit

Analysis of Autophagy-Related Signatures Identified Two Distinct Subtypes for Evaluating the Tumor Immune Microenvironment and Predicting Prognosis in Ovarian Cancer

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