Prognostic Variables for Cancer-Related Survival in Node-Negative Colorectal Carcinomas

Fabio, Francesco Di; Nascimbeni, Riccardo; Villanacci, Vincenzo; Baronchelli, Carla; Bianchi, Denise; Fabbretti, Giovanna; Casella, Claudio; Salerni, Bruno

doi:10.1159/000077348

Cited by 29 publications

(15 citation statements)

References 19 publications

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“…In addition, this study showed that age pathological T, and tumor recurrence were independent prognostic factors in patients with colon cancer. Consistent with our results, previous studies have also demonstrated that advanced age, higher pathological T and tumor recurrence are associated with poor prognosis in patients with colon cancer (31)(32)(33). Notably, this study revealed that the results of the prognostic model were consistent with actual survival prognostic information in different groups based on hierarchical analysis of age, higher pathological T and tumor recurrence.…”

Section: Discussionsupporting

confidence: 92%

The identification of a potential prognostic model of colon cancer using integrated bioinformatics analysis

Fang

Xie

et al. 2020

Preprint

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Abstract Background This study aimed to construct prognostic model by screening prognostic gene signature of colon cancer. Methods The gene expression profile data of colon cancer were obtained from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) and differently expressed genes (DEGs) between tumor and control samples were identified. Prognosis-associated genes were then identified and used for the construction of prognostic model. The independent factors that associated with the prognosis of colon in the TCGA cohort was identified. Results Totally, 1153 consistent DEGs were screened out between tumor and normal tissues in the TCGA cohort, GSE44861 and GSE44076 datasets. Among these genes, 12 DEGs were related to the prognosis of colon cancer and were used for constructing the prognostic model. This model presented a high predictive power for the prognosis of colon cancer both in the training dataset and in the validation datasets (AUC > 0.8). Statistical analysis showed that age, pathological T, tumor recurrence, and model status were the independent factors for prognosis of patients with colon cancer in TCGA. Conclusions The 12-gene signature prognostic model had a high predictive power for colon cancer prognosis.

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Section: Discussionsupporting

confidence: 92%

The identification of a potential prognostic model of colon cancer using integrated bioinformatics analysis

Fang

Xie

et al. 2020

Preprint

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“…In an analysis of 124 patients with lymph node‐negative colorectal cancer who underwent curative resection, the 5‐year survival rate was 87% for patients with PNI‐negative tumors versus 57% for patients with PNI‐positive tumors ( P < .006) 86. Other studies similarly have indicated that positive PNI status portends a worse outcome in patients with lymph node‐negative colorectal tumors 87‐89. This suggests that PNI indicates a more aggressive tumor phenotype and may be useful in selecting a subgroup of lymph node‐negative patients who could benefit from adjuvant therapy.…”

Section: Clinical Significancementioning

confidence: 99%

Perineural invasion in cancer

Liebig

Ayala

Wilks

et al. 2009

Cancer

936

414

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Perineural invasion (PNI) is the process of neoplastic invasion of nerves and is an under-recognized route of metastatic spread. It is emerging as an important pathologic feature of many malignancies, including those of the pancreas, colon and rectum, prostate, head and neck, biliary tract, and stomach. For many of these malignancies, PNI is a marker of poor outcome and a harbinger of decreased survival. PNI is a distinct pathologic entity that can be observed in the absence of lymphatic or vascular invasion. It can be a source of distant tumor spread well beyond the extent of any local invasion; and, for some tumors, PNI may be the sole route of metastatic spread. Despite increasing recognition of this metastatic process, there has been little progress in the understanding of molecular mechanisms behind PNI and, to date, no targeted treatment modalities aimed at this pathologic entity. The objectives of this review were to lay out a clear definition of PNI to highlight its significance in those malignancies in which it has been studied best. The authors also summarized current theories on the molecular mediators and pathogenesis of PNI and introduced current research models that are leading to advancements in the understanding of this meta- A key feature of malignant cells is their ability to dissociate from the primary tumor and to establish metastatic deposits at distant sites. Vascular and lymphatic channels are well accepted routes of metastatic spread. They are well characterized in the literature and are the focus of much current research on tumor biology. However, another route of tumor spread that occurs in and along nerves has been described in the literature since the mid-1800s but has received relatively little research attention. Perineural invasion (PNI) is the process of neoplastic invasion of nerves. It also has been called neurotropic carcinomatous spread and perineural spread. PNI was reported first in the European literature by scientists who described head and neck cancers that exhibited a predilection for growth along nerves as they made their way toward the intracranial fossa.1,2 PNI has emerged since then as a key pathologic feature of many other malignancies, including those of the pancreas, colon and rectum, prostate, biliary tract, and stomach. For many of these malignancies, PNI is a marker of poor outcome and a harbinger of decreased survival.3-7

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“…7 The prognostic significance of PNI is widely advocated in malignancies of the head and neck and prostate, [8][9][10] but controversies exist in colorectal cancer. [11][12][13][14] In T1-2 early rectal cancer, PNI is one of the adverse pathologic features in selecting patients undergoing local excision. But whether it can be used as a criterion to select patients receiving chemoradiotherapy in T3N0 patients is still unknown to us.…”

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confidence: 99%

Perineural invasion in pT3N0 rectal cancer

Peng

Sheng

Huang

et al. 2010

Cancer

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BACKGROUND:The authors' purpose was to explore the incidence and prognostic significance of perineural invasion (PNI) in pT3N0 rectal cancer. METHODS: Pathologic materials from resected specimens of 173 patients with pT3N0 rectal cancer were retrospectively collected. PNI-positivity was categorized into 2 groups: surrounding the nerve sheath (SS-PNI) and invading through the nerve sheath (TS-PNI). The rate of PNI-positivity was compared with PNI as initially recorded in the original reports. Patients' outcome was studied in groups with different PNI status, and multivariate analysis was performed to determine its prognostic value. RESULTS: In this retrospective analysis, PNIpositivity was found in 24.3% of all cases, in which SS-PNI and TS-PNI were 11% and 13.3%, respectively, and was related to lymphovascular invasion. Only 7.5% of patients' specimens were reported as PNI-positive in the original reports. Detection of SS-PNI was likelier to be missed than TS-PNI. The rates of local recurrence, disease-free survival, and overall survival at 5 years were similar between the groups of SS-PNI and TS-PNI. The 5-year local recurrence rate was more than 2.5-fold higher in the PNI-positive group compared with the PNI-negative group (22.7% vs 7.9%, respectively; P ¼ .017). Multivariate analysis proved that PNI-positivity was the only independent risk factor for predicting 5-year local recurrence rate, whereas only sampled lymph nodes was related to 5-year disease-free survival and overall survival. CONCLUSIONS: PNI is a common pathologic feature in rectal cancer. The definition of PNI should include SS-PNI and TS-PNI. Rectal cancer patients who are PNI-positive are at higher risk of local recurrence and should be considered for more intensive treatment.

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Prognostic Variables for Cancer-Related Survival in Node-Negative Colorectal Carcinomas

Cited by 29 publications

References 19 publications

The identification of a potential prognostic model of colon cancer using integrated bioinformatics analysis

The identification of a potential prognostic model of colon cancer using integrated bioinformatics analysis

Perineural invasion in cancer

Perineural invasion in pT3N0 rectal cancer

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