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Cancers
Special Issues
Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers
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Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 22469

Special Issue Editor

Dr. Caroline Bascoul-Mollevi

E-Mail Website
Guest Editor
1. Biometrics Unit, Montpellier Cancer Institute (ICM), Univ Montpellier, 208 rue des Apothicaires, 34298 Montpellier, France
2. Desbrest Institute of Epidemiology and Public Health (IDESP), UMR Inserm – Univ Montpellier, Montpellier, France
Interests: statistics; oncology; clinical trials; longitudinal analysis; joint model; health-related quality of life; patient-reported outcomes

Special Issue Information

Dear Colleagues,

Biomarkers are used in cancer research more and more due to new technological developments or the concept of personalized medicine. These biomarkers are mainly of three types: diagnostic biomarkers, companion biomarkers—used in combination with specific therapies—that help to predict response or occurrence of severe toxicity, and prognostic biomarkers. The study of these biomarkers is revealed to be particularly useful for treatment management or monitoring of patients suffering from cancer.

Recent statistical methods have been specifically developed to study the impact of the trajectory of a biomarker, i.e., of a biomarker assessed repeatedly over time, on the risk of a clinical event. For example, joint models which combine a linear mixed (sub-)model (for the longitudinal biomarker) and a survival (sub-)model (for the time-to-event) are an interesting approach to improve prediction of progression/death using a longitudinal biomarker. Time-dependent ROC curve analysis has also been proposed to improve diagnostic accuracy, i.e., the ability of a biomarker to discriminate between healthy and diseased individuals, considering a disease status which may change over time.

In this Special Issue, experts will focus on approaches using biomarkers (with repeated measurements or not) to predict the occurrence of a time-dependent event such as the disease (diagnosis), or toxicities (prediction), or death (prognostic). Special attention will be paid to articles implying innovative statistical methods.

Dr. Caroline Bascoul-Mollevi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomarkers
  • diagnosis
  • prediction
  • prognosis
  • time-dependent ROC curve
  • joint model
  • linear-mixed model
  • time-to-event data analysis

Published Papers (11 papers)

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Research

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25 pages, 7731 KiB  
Article
Pan-Cancer Profiling of Intron Retention and Its Clinical Significance in Diagnosis and Prognosis
by Leihuan Huang, Xin Zeng, Haijing Ma, Yu Yang, Yoshie Akimoto, Gang Wei and Ting Ni
Cancers 2023, 15(23), 5689; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15235689 - 01 Dec 2023
Viewed by 1074
Abstract
Alternative splicing can produce transcripts that affect cancer development and thus shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been studied less in cancer biology research. Here, we generated a pan-cancer IR landscape for [...] Read more.
Alternative splicing can produce transcripts that affect cancer development and thus shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been studied less in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention inside the 5′UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification in certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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13 pages, 1744 KiB  
Article
The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors
by Islam Eljilany, Payman Ghasemi Saghand, James Chen, Aakrosh Ratan, Martin McCarter, John Carpten, Howard Colman, Alexandra P. Ikeguchi, Igor Puzanov, Susanne Arnold, Michelle Churchman, Patrick Hwu, Jose Conejo-Garcia, William S. Dalton, George J. Weiner, Issam M. El Naqa and Ahmad A. Tarhini
Cancers 2023, 15(20), 4913; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15204913 - 10 Oct 2023
Viewed by 1982
Abstract
Background: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference [...] Read more.
Background: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. Methods: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan–Meier curves. The OS predictions were assessed using Harrell’s concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. Results: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate–high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. Conclusions: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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11 pages, 1386 KiB  
Article
Time-Dependent ROC Curve Analysis for Assessing the Capability of Radiation-Induced CD8 T-Lymphocyte Apoptosis to Predict Late Toxicities after Adjuvant Radiotherapy of Breast Cancer Patients
by Célia Touraine, Audrey Winter, Florence Castan, David Azria and Sophie Gourgou
Cancers 2023, 15(19), 4676; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15194676 - 22 Sep 2023
Cited by 1 | Viewed by 897
Abstract
Late fibrosis can occur in breast cancer patients treated with curative-intent radiotherapy. Predicting this toxicity is of clinical interest in order to adapt the irradiation dose delivered. Radiation-induced CD8 T-lymphocyte apoptosis (RILA) had been proven to be associated with less grade ≥2 late [...] Read more.
Late fibrosis can occur in breast cancer patients treated with curative-intent radiotherapy. Predicting this toxicity is of clinical interest in order to adapt the irradiation dose delivered. Radiation-induced CD8 T-lymphocyte apoptosis (RILA) had been proven to be associated with less grade ≥2 late radiation-induced toxicities in patients with miscellaneous cancers. Tobacco smoking status and adjuvant hormonotherapy were also identified as potential factors related to late-breast-fibrosis-free survival. This article evaluates the predictive performance of the RILA using a ROC curve analysis that takes into account the dynamic nature of fibrosis occurrence. This time-dependent ROC curve approach is also applied to evaluate the ability of the RILA combined with the other previously identified factors. Our analysis includes a Monte Carlo cross-validation procedure and the calculation of an expected cost of misclassification, which provides more importance to patients who have no risk of late fibrosis in order to be able to treat them with the maximal irradiation dose. Performance evaluation was assessed at 12, 24, 36 and 50 months. At 36 months, our results were comparable to those obtained in a previous study, thus underlying the predictive power of the RILA. Based on specificity and cost, RILA alone seemed to be the most performant, while its association with the other factors had better negative predictive value results. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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18 pages, 2476 KiB  
Article
Cancer Associated Macrophage-like Cells Are Prognostic for Highly Aggressive Prostate Cancer in Both the Non-Metastatic and Metastatic Settings
by Daniel J. Gironda, Raymond C. Bergan, R. Katherine Alpaugh, Daniel C. Danila, Tuan L. Chuang, Brenda Y. Hurtado, Thai Ho and Daniel L. Adams
Cancers 2023, 15(14), 3725; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15143725 - 22 Jul 2023
Viewed by 1268
Abstract
Despite advancements in the early-stage detection and expansion of treatments for prostate cancer (PCa), patient mortality rates remain high in patients with aggressive disease and the overtreatment of indolent disease remains a major issue. Prostate-specific antigen (PSA), a standard PCa blood biomarker, is [...] Read more.
Despite advancements in the early-stage detection and expansion of treatments for prostate cancer (PCa), patient mortality rates remain high in patients with aggressive disease and the overtreatment of indolent disease remains a major issue. Prostate-specific antigen (PSA), a standard PCa blood biomarker, is limited in its ability to differentiate disease subtypes resulting in the overtreatment of non-aggressive indolent disease. Here we assess engorged cancer-associated macrophage-like cells (CAMLs), a ≥50 µm, cancer-specific, polynucleated circulating cell type found in the blood of patients with PCa as a potential companion biomarker to PSA for patient risk stratification. We found that rising PSA is positively correlated with increasing CAML size (r = 0.307, p = 0.004) and number of CAMLs in circulation (r = 0.399, p < 0.001). Over a 2-year period, the presence of a single engorged CAML was associated with 20.9 times increased likelihood of progression (p = 0.016) in non-metastatic PCa, and 2.4 times likelihood of progression (p = 0.031) with 5.4 times likelihood of death (p < 0.001) in metastatic PCa. These preliminary data suggest that CAML cell monitoring, in combination with PSA, may aid in differentiating non-aggressive from aggressive PCas by adding biological information that complements traditional clinical biomarkers, thereby helping guide treatment strategies. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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14 pages, 19502 KiB  
Article
CA-125 Early Dynamics to Predict Overall Survival in Women with Newly Diagnosed Advanced Ovarian Cancer Based on Meta-Analysis Data
by Eleni Karamouza, Rosalind M. Glasspool, Caroline Kelly, Liz-Anne Lewsley, Karen Carty, Gunnar B. Kristensen, Josee-Lyne Ethier, Tatsuo Kagimura, Nozomu Yanaihara, Sabrina Chiara Cecere, Benoit You, Ingrid A. Boere, Eric Pujade-Lauraine, Isabelle Ray-Coquard, Cécile Proust-Lima and Xavier Paoletti
Cancers 2023, 15(6), 1823; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers15061823 - 17 Mar 2023
Cited by 2 | Viewed by 2227
Abstract
(1) Background: Cancer antigen 125 (CA-125) is a protein produced by ovarian cancer cells that is used for patients’ monitoring. However, the best ways to analyze its decline and prognostic role are poorly quantified. (2) Methods: We leveraged individual patient data from the [...] Read more.
(1) Background: Cancer antigen 125 (CA-125) is a protein produced by ovarian cancer cells that is used for patients’ monitoring. However, the best ways to analyze its decline and prognostic role are poorly quantified. (2) Methods: We leveraged individual patient data from the Gynecologic Cancer Intergroup (GCIG) meta-analysis (N = 5573) to compare different approaches summarizing the early trajectory of CA-125 before the prediction time (called the landmark time) at 3 or 6 months after treatment initiation in order to predict overall survival. These summaries included observed and estimated measures obtained by a linear mixed model (LMM). Their performances were evaluated by 10-fold cross-validation with the Brier score and the area under the ROC (AUC). (3) Results: The estimated value and the last observed value at 3 months were the best measures used to predict overall survival, with an AUC of 0.75 CI 95% [0.70; 0.80] at 24 and 36 months and 0.74 [0.69; 0.80] and 0.75 [0.69; 0.80] at 48 months, respectively, considering that CA-125 over 6 months did not improve the AUC, with 0.74 [0.68; 0.78] at 24 months and 0.71 [0.65; 0.76] at 36 and 48 months. (4) Conclusions: A 3-month surveillance provided reliable individual information on overall survival until 48 months for patients receiving first-line chemotherapy. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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15 pages, 1456 KiB  
Article
MicroRNA Expression Profiling Predicts Nodal Status and Disease Recurrence in Patients Treated with Curative Intent for Colorectal Cancer
by Matthew G. Davey, Gerard Feeney, Heidi Annuk, Maxwell Paganga, Emma Holian, Aoife J. Lowery, Michael J. Kerin and Nicola Miller
Cancers 2022, 14(9), 2109; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14092109 - 23 Apr 2022
Cited by 11 | Viewed by 2008
Abstract
Background: Approximately one-third of colorectal cancer (CRC) patients will suffer recurrence. MiRNAs are small non-coding RNAs that play important roles in gene expression. We aimed to correlate miRNA expression with aggressive clinicopathological characteristics and survival outcomes in CRC. Methods: Tumour samples were extracted [...] Read more.
Background: Approximately one-third of colorectal cancer (CRC) patients will suffer recurrence. MiRNAs are small non-coding RNAs that play important roles in gene expression. We aimed to correlate miRNA expression with aggressive clinicopathological characteristics and survival outcomes in CRC. Methods: Tumour samples were extracted from 74 CRC patients. MiRNAs were quantified using real-time reverse transcriptase polymerase chain reaction. Descriptive statistics and Cox regression analyses were performed to correlate miRNA targets with clinicopathological and outcome data. Results: Aberrant miR-21 and miR-135b expression correlate with increased nodal stage (p = 0.039, p = 0.022). Using univariable Cox regression analyses, reduced miR-135b (β-coefficient −1.126, hazard ratio 0.324, standard error (SE) 0.4698, p = 0.017) and increased miR-195 (β-coefficient 1.442, hazard ratio 4.229, SE 0.446, p = 0.001) predicted time to disease recurrence. Survival regression trees analysis illustrated a relative cut-off of ≤0.488 for miR-195 and a relative cut-off of >−0.218 for miR-135b; both were associated with improved disease recurrence (p < 0.001, p = 0.015). Using multivariable analysis with all targets as predictors, miR-195 (β-coefficient 3.187, SE 1.419, p = 0.025) was the sole significant independent predictor of recurrence. Conclusion: MiR-195 has strong value in predicting time to recurrence in CRC patients. Additionally, miR-21 and miR-135b predict the degree nodal burden. Future studies may include these findings to personalize therapeutic and surgical decision making. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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12 pages, 2215 KiB  
Article
Comparison of Immune Response Assessment in Colon Cancer by Immunoscore (Automated Digital Pathology) and Pathologist Visual Scoring
by Isabelle Boquet, Alboukadel Kassambara, Alfred Lui, Alicia Tanner, Marie Latil, Yoann Lovera, Fanny Arnoux, Fabienne Hermitte, Jérôme Galon and Aurelie Catteau
Cancers 2022, 14(5), 1170; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14051170 - 24 Feb 2022
Cited by 6 | Viewed by 1797
Abstract
Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based [...] Read more.
Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists’ disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists’ classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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17 pages, 2699 KiB  
Article
Longitudinal Analysis of 1α,25-dihidroxyvitamin D3 and Homocysteine Changes in Colorectal Cancer
by Dorottya Mühl, Magdolna Herold, Zoltan Herold, Lilla Hornyák, Attila Marcell Szasz and Magdolna Dank
Cancers 2022, 14(3), 658; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14030658 - 28 Jan 2022
Viewed by 1768
Abstract
Background: 1α,25-dihydroxycholecalciferol (1,25(OH)2D3) and homocysteine are known to play a role in the pathophysiology of colorectal cancer (CRC). In health, the two changes are inversely proportional to each other, but little is known about their combined effect in CRC. [...] Read more.
Background: 1α,25-dihydroxycholecalciferol (1,25(OH)2D3) and homocysteine are known to play a role in the pathophysiology of colorectal cancer (CRC). In health, the two changes are inversely proportional to each other, but little is known about their combined effect in CRC. Methods: The serum 1,25(OH)2D3 and the homocysteine levels of eighty-six CRC patients were measured, who were enrolled into four cohorts based on the presence of metastases (Adj vs. Met) and vitamin D3 supplementation (ND vs. D). Results: 1,25(OH)2D3 was constant (Adj-ND), increased significantly (Adj-D, p = 0.0261), decreased (Met-ND), or returned close to the baseline after an initial increase (Met-D). The longitudinal increase in 1,25(OH)2D3 (HR: 0.9130, p = 0.0111) positively affected the overall survival in non-metastatic CRC, however, this effect was cancelled out in those with metastasis (p = 0.0107). The increase in homocysteine negatively affected both the overall (HR: 1.0940, p = 0.0067) and the progression-free survival (HR: 1.0845, p = 0.0073). Lower 1,25(OH)2D3 and/or higher homocysteine level was characteristic for patients with higher serum lipids, albumin, total protein, white blood cell and platelet count, male sex, and right-sided tumors. No statistically justifiable connection was found between the target variables. Conclusions: A measurement-based titration of vitamin D3 supplementation and better management of comorbidities are recommended for CRC. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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12 pages, 1334 KiB  
Article
(Pro)renin Receptor Is a Novel Independent Prognostic Marker in Invasive Urothelial Carcinoma of the Bladder
by Gorka Larrinaga, Julio Calvete-Candenas, Jon Danel Solano-Iturri, Ana M. Martín, Angel Pueyo, Caroline E. Nunes-Xavier, Rafael Pulido, Juan F. Dorado, José I. López and Javier C. Angulo
Cancers 2021, 13(22), 5642; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13225642 - 11 Nov 2021
Cited by 4 | Viewed by 2267
Abstract
(Pro)renin receptor (PRR) is being investigated in several malignancies as it activates pathogenic pathways that contribute to cell proliferation, immunosuppressive microenvironments, and acquisition of aggressive neoplastic phenotypes. Its implication in urothelial cancer (UC) has not been evaluated so far. We retrospectively evaluate the [...] Read more.
(Pro)renin receptor (PRR) is being investigated in several malignancies as it activates pathogenic pathways that contribute to cell proliferation, immunosuppressive microenvironments, and acquisition of aggressive neoplastic phenotypes. Its implication in urothelial cancer (UC) has not been evaluated so far. We retrospectively evaluate the prognostic role of PRR expression in a series of patients with invasive UC treated with radical cystectomy and other clinical and histopathological parameters including p53, markers of immune-checkpoint inhibition, and basal and luminal phenotypes evaluated by tissue microarray. Cox regression analyses using stepwise selection evaluated candidate prognostic factors and disease-specific survival. PRR was expressed in 77.3% of the primary tumors and in 70% of positive lymph nodes. PRR expression correlated with age (p = 0.006) and was associated with lower preoperatively hemoglobin levels. No other statistical association was evidenced with clinical and pathological variables (gender, ASA score, Charlson comorbidity index, grade, pT, pN) or immunohistochemical expressions evaluated (CK20, GA-TA3, CK5/6, CD44, PD-L1, PD-1, B7-H3, VISTA, and p53). PRR expression in primary tumors was associated with worse survival (log-rank, p = 0.008). Cox regression revealed that PRR expression (HR 1.85, 95% CI 1.22–2.8), pT (HR 7.02, 95% CI 2.68–18.39), pN (HR 2.3, 95% CI 1.27–4.19), and p53 expression (HR 1.95, 95% CI 1.1–3.45) were independent prognostic factors in this series. In conclusion, we describe PRR protein and its prognostic role in invasive UC for the first time. Likely mechanisms involved are MAPK/ERK activation, Wnt/β-catenin signaling, and v-ATPAse function. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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12 pages, 1016 KiB  
Article
Impact of Serum γ-Glutamyltransferase on Overall Survival in Men with Metastatic Castration-Resistant Prostate Cancer Treated with Docetaxel
by Minami Une, Kosuke Takemura, Kentaro Inamura, Hiroshi Fukushima, Masaya Ito, Shuichiro Kobayashi, Takeshi Yuasa, Junji Yonese, Philip G. Board and Fumitaka Koga
Cancers 2021, 13(21), 5587; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers13215587 - 08 Nov 2021
Cited by 1 | Viewed by 1902
Abstract
Background: Reports on the prognostic significance of serum γ-glutamyltransferase (GGT) in men with metastatic castration-resistant prostate cancer (mCRPC) are limited. In addition, GGT expression status in cancer tissues has not been well characterized regardless of cancer types. Methods: This retrospective study included 107 [...] Read more.
Background: Reports on the prognostic significance of serum γ-glutamyltransferase (GGT) in men with metastatic castration-resistant prostate cancer (mCRPC) are limited. In addition, GGT expression status in cancer tissues has not been well characterized regardless of cancer types. Methods: This retrospective study included 107 consecutive men with mCRPC receiving docetaxel therapy. The primary endpoints were associations of serum GGT with overall survival (OS) and prostate-specific antigen (PSA) response. The secondary endpoint was an association of serum GGT with progression-free survival (PFS). Additionally, GGT expression status was immunohistochemically semi-quantified using tissue microarrays. Results: A total of 67 (63%) men died during follow-up periods (median 22.5 months for survivors). On multivariable analysis, high Log GGT was independently associated with adverse OS (HR 1.49, p = 0.006) as were low hemoglobin (HR 0.79, p = 0.002) and high PSA (HR 1.40, p < 0.001). In contrast, serum GGT was not significantly associated with PSA response or PFS. Moreover, incorporation of serum GGT into established prognostic models (i.e., Halabi and Smaletz models) increased their C-indices for predicting OS from 0.772 to 0.787 (p = 0.066) and from 0.777 to 0.785 (p = 0.118), respectively. Furthermore, there was a positive correlation between serum and tissue GGT levels (ρ = 0.53, p = 0.003). Conclusions: Serum GGT may be a prognostic biomarker in men with mCRPC receiving docetaxel therapy. GGT overexpression by prostate cancer cells appears to be responsible for the elevation of GGT in the serum. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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Review

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17 pages, 1872 KiB  
Review
The Increasing Prognostic and Predictive Roles of the Tumor Primary Chemosensitivity Assessed by CA-125 Elimination Rate Constant K (KELIM) in Ovarian Cancer: A Narrative Review
by Ambroise Lauby, Olivier Colomban, Pauline Corbaux, Julien Peron, Lilian Van Wagensveld, Witold Gertych, Naoual Bakrin, Pierre Descargues, Jonathan Lopez, Vahan Kepenekian, Olivier Glehen, Charles Andre Philip, Mojgan Devouassoux-Shisheboran, Michel Tod, Gilles Freyer and Benoit You
Cancers 2022, 14(1), 98; https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14010098 - 25 Dec 2021
Cited by 16 | Viewed by 4039
Abstract
Ovarian cancer is the gynecological cancer with the worst prognosis and the highest mortality rate because 75% of patients are diagnosed with advanced stage III–IV disease. About 50% of patients are now treated with neoadjuvant chemotherapy followed by interval debulking surgery (IDS). In [...] Read more.
Ovarian cancer is the gynecological cancer with the worst prognosis and the highest mortality rate because 75% of patients are diagnosed with advanced stage III–IV disease. About 50% of patients are now treated with neoadjuvant chemotherapy followed by interval debulking surgery (IDS). In that context, there is a need for accurate predictors of tumor primary chemosensitivity, as it may impact the feasibility of subsequent IDS. Across seven studies with more than 12,000 patients, including six large randomized clinical trials and a national cancer registry, along with a mega-analysis database with 5842 patients, the modeled CA-125 ELIMination rate constant K (KELIM), the calculation of which is based on the longitudinal kinetics during the first three cycles of platinum-based chemotherapy, was shown to be a reproducible indicator of tumor intrinsic chemosensitivity. Indeed, KELIM is strongly associated with the likelihood of complete IDS, subsequent platinum-free interval, progression-free survival, and overall survival, along with the efficacy of maintenance treatment with bevacizumab or veliparib. As a consequence, KELIM might be used to guide more subtly the medical and surgical treatments in a first-line setting. Moreover, it could be used to identify the patients with poorly chemosensitive disease, who will be the best candidates for innovative treatments meant to reverse the chemoresistance, such as cell cycle inhibitors or immunotherapy. Full article
(This article belongs to the Special Issue Analyze Cancer Screening and Make Predictions and Prognoses Using Biomarkers)
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