| Literature DB >> 26446626 |
Nam Kyu Kim1, Hyuk Hur2.
Abstract
Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10-30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment.Entities:
Keywords: Rectal neoplasms; biological markers; chemoradiotherapy
Mesh:
Substances:
Year: 2015 PMID: 26446626 PMCID: PMC4630032 DOI: 10.3349/ymj.2015.56.6.1461
Source DB: PubMed Journal: Yonsei Med J ISSN: 0513-5796 Impact factor: 2.759
Fig. 1Primary tumor response after preoperative chemoradiation therapy for rectal cancer. (A) Complete pathologic response. (B) Poor response. The arrow indicates the residual tumor.
Fig. 2Systemic progression of disease during preoperative chemoradiation therapy. The arrow indicates the liver metastasis (A) and the paraaortic lymph node metastasis (B).
Fig. 3Various endoscopic findings of primary tumors after preoperative chemoradiation therapy. (A) Whitening of the mucosa. (B) Association of telangiectasia. (C) Deep ulceration. (D) Palpable nodule.
Fig. 4Various findings according to MRI after preoperative chemoradiation therapy for rectal cancer. Good response: (A) MRI before preoperative CRT; (B) MRI after preoperative CRT. Poor response: (C) MRI before preoperative CRT; (D) MRI after preoperative CRT. CRT, chemoradiation therapy.
Fig. 5Perfusion MRI imaging. (A) Good response. (B) Poor response.
Recent Studies of SUV as a Predictor of Responses to CRT among Patients with LARC
| Ref. | No. | Parameter | Sensitivity (%) | Specificity (%) | Cut-off value | Conclusion |
|---|---|---|---|---|---|---|
| Amthauer, et al. | 22 | ΔSUVmax | 93 | 100 | 36% | ΔSUVmax was significantly greater in responders than in non-responders. |
| Hur, et al. | 37 | SUVmax-post | 84.6 | 79.2 | 3.35 | SUV-post and RR were significantly associated with pathological treatment response, especially in pCR. |
| Capirci, et al. | 87 | RI | 84.5 | 80 | 65% | RI was the best predictor of CRT response. |
| Martoni, et al. | 80 | SUVmax-post | 88 | 34 | 5.0 | SUVmax-post supplied limited predictive information. |
| RI | 94 | 31 | 66% | |||
| Maffione, et al. | 69 | SUVmax-post | 85.4 | 80 | 5.1 | SUVmax, MTV and TLG after CRT, RI, ΔMTV%, and ΔTLG% parameters were significantly correlated with pathological treatment response. SUVmax-post demonstrated the highest AUC, sensitivity, and specificity. |
| MTVpost | 86.7 | 80 | 2.1 cm3 | |||
| TLGpost | 65.3 | 75 | 23.4 cm3 | |||
| RI | 85.7 | 70 | 61.8% | |||
| ΔMTV% | 83.7 | 80 | 81.4% | |||
| ΔTLG | 69.4 | 80 | 94.2% | |||
| VRA | 69 | 55 |
SUV, standardized uptake value; CRT, chemoradiotherapy; LARC, locally advanced rectal cancer; pCR, pathological complete response; SUVmean, mean SUV; SUVmax, maximum SUV; SUVmean-post, mean SUV of post CRT; SUVmax-post, maximum SUV of post CRT; ΔSUVmax, SUVmax-pre-SUVmax-post; RI, response index (SUVpre-SUVpost)/SUVpre; MTV, metabolic tumor volume; ΔMTV%, (MTVpre-MTVpost)/MTVpre; TLG, total lesion glycolysis (SUVmean×MTV); VRA, visual response assessment.
Fig. 618F-FDG PET before and after preoperative chemoradiation therapy for rectal cancer. (A) Before and (B) after in a pathologic complete response case. (C) Before and (D) after in a poor response case. 18F-FDG PET, fluorine-18-fluorodeoxyglucose/positron emission tomography.
Recent Studies of CEA as a Predictor of Responses to CRT among Patients with LARC
| Ref. | No. | Parameter | Cut-off value | Conclusion | |
|---|---|---|---|---|---|
| Park, et al. | 352 | CEA-pre | 3 ng/mL | <0.001 | CEA-pre level is of clinical value as a predictor of response to pre-CRT. |
| CEA-pre | 3.4 ng/mL | 0.008 | Low CEA-pre was significantly associated with pCR. | ||
| Lee, et al. | 345 | CEA-pre | 5 ng/mL | 0.002 | CEA-pre was significant for prediction of pCR. |
| Perez, et al. | 170 | CEA-post | 5 ng/mL | 0.009 (clinical CR) | Low CEA-pre level was associated with an increased rate of cCR but not with pCR. |
| CEA-pre | 0.05 (pCR) | ||||
| CEA-reduction | 5 ng/mL | ||||
| Jang, et al. | 109 | CEA-post | 2.7 ng/mL | 0.015 (clinical CR) | CEA-post was an independent predictor of good tumor regression. |
| 0.06 (pCR) | |||||
| Yang, et al. | 138 | CEA-post | 2.61 ng/mL | 0.001 | CEA-post <2.61 ng/mL predicted pCR (sensitivity 76.0%, specificity 58.4%), CEA ratio predicted pCR (sensitivity 87.5%, specificity 76.7%) for those with CEA-pre ≥6 ng/mL. |
| CEA-ratio | 0.22 ng/mL |
CEA, carcinoembryonic antigen; CRT, chemoradiotherapy; LARC, locally advanced rectal cancer; pCR, pathological complete response; CEA-pre, pretreatment CEA (CEA-pre) level; CEA-post, post-CRT CEA level; CEA ratio, CEA-post divided by CEA-pre; CEA-reduction, CEA-pre-CEA-post.
Biomarkers and Analysis Methods for Prediction of Responses to Preoperative CRT among Patients with LARC
| Ref. | No. | Biomarker | Analysis method | Conclusion | |
|---|---|---|---|---|---|
| Komuro, et al. | 111 | p53 | IHC | 0.045 | There was a significant correlation between the expression pattern of p53 and tumor radiosensitivity. |
| Fu, et al. | 49 | p53 | IHC | 0.01 | The majority of p53(-) or p21(+) tumors were radiosensitive. |
| p21 | |||||
| Huh, et al. | 123 | 13 markers | PCR | 0.03 | Only CD44 expression was found to be a significant independent predictive factor of tumor regression grade response. |
| Rau, et al. | 66 | p53, p21, Ki67 | PCR | Lower p21 expression in pre-treatment biopsies was correlated with poor response. | |
| Kim, et al. | 183 | EGFR | IHC | 0.012 | The significant predictive factor for increased tumor down staging was a low level of EGFR expression. |
| Zlobec, et al. | 104 | EGFR | IHC | 0.01 | Loss of VEGF and positive EGFR are independent predictors of pCR. |
| VEGF | 0.009 | ||||
| Spindler, et al. | 77 | EGFR | IHC | >0.05 | EGFR Sp1-216G/T polymorphism is a potential marker of response to CRT. |
| SNP | 0.023 | ||||
| Sprenger, et al. | 126 | CD133 | IHC | <0.01 | Increased fraction of CD133-expressing cells after preoperative CRT was associated with less histopathologic tumor regression. |
| Havelund, et al. | 50 | HIF-1α | IHC | There were no significant differences between the HIF-1α-positive group and HIF-1α-negative group with regard to pathological grading and pCR. |
CRT, chemoradiotherapy; LARC, locally advanced rectal cancer; pCR, pathological complete response; GE, gene expression; IHC, immunohistochemistry; PCR, polymerase chain reaction; TRG, tumor regression grade; EGFR, epidermal growth factor receptor; VEGF, vascular endothelial growth factor; SNP, single-nucleotide polymorphisms; HIF-1α, hypoxia-inducible factor 1α; GLUT-1, glucose transporter-1.
Recent Studies Using Gene Expression Profiling to Analyze the Genetics of Response to CRT among Patients with LARC
| Ref. | No. | No. of genes | Accuracy (%) | Conclusion |
|---|---|---|---|---|
| Ghadimi, et al. | 30 | 54 | 82.4 | Pretherapeutic gene expression profiling might assist in response prediction to preoperative CRT. |
| Watanabe, et al. | 52 | 33 | 82.4 | Gene expression profiling might be useful in predicting response to radiotherapy. |
| Kim, et al. | 46 | 95 | 84 | Microarray gene expression analysis was successfully used to predict CR to preoperative CRT. |
| Rimkus, et al. | 43 | 42 | 86 | Pretherapeutic prediction of response to CRT based on gene expression analysis represents a new valuable and practical tool for therapeutic stratification. |
| Nishioka, et al. | 17 | 17 | Gene expression patterns of diagnostic biopsies can predict pathological response to preoperative CRT. | |
| Supiot, et al. | 6 | 31 (up) | Micro-arrays can efficiently assess early transcriptomic changes during preoperative radiotherapy for rectal cancer. | |
| 6 (down) |
CRT, chemoradiotherapy; LARC, locally advanced rectal cancer; CR, complete response.
Fig. 7Direct invasion of seminal vesicles and prostate gland with a positive circumferential resection margin after preoperative CRT. The arrow indicates tumor before preoperative CRT (A) and after preoperative CRT (B). CRT, chemoradiation therapy.