We read with interest Dr. Włodarczyk and Professor Kużdżał’s appraisal of the potential for composite positron emission tomography-computed tomography (PET-CT) metrics to improve the assessment of oesophageal cancer to neoadjuvant therapy, in particular that of a new metric we recently described: metabolic nodal response (mNR) (1,2).
Our colleagues highlight the goal of precision oncology for oesophageal cancer: tailoring therapies to patients. At present, whilst neoadjuvant therapy improves survival for patients overall (3), this is not necessarily true for patients individually. Unfortunately, those with relatively chemo- and radio-resistant tumours may actually come to harm, as ultimately futile therapy merely delays surgery and risks toxicity. However, in the absence of markers to identify these patients we are forced to continue with well-intentioned but largely imprecise oncology.
The reasons precision oncology has largely failed to translate in vitro reports to in vivo success (other than relatively isolated therapies targeted to individual gene mutations and copy numbers) are numerous (4). These include highly complex molecular interactions in individual cancer cells (genetic, epigenetic, transcriptomic, proteomic), compounded by cellular interactions, tumour microenvironment, clonal heterogeneity, and tumour evolution during therapy (5). As a consequence, the effect sizes of these markers tend to be limited, and certainly an insufficient basis on which to decide whether to give or omit specific therapies (6).
We are therefore forced to rely on surrogates of response, such as metabolic response using serial 18F-FDG PET-CT. As our colleagues discuss, Lordick et al. notably described interval assessment of oesophageal cancer during neoadjuvant chemotherapy, aborting or continuing therapy on the basis of whether the primary tumour demonstrated a metabolic response on PET-CT, as evidenced by a reduction in avidity alone (7). This approach has yet to be adopted for a number of reasons, including concerns regarding the inherent limitations of PET-CT to accurately reflect the viability and metastatic potential of tumour cells, as well as the pragmatic but somewhat arbitrary dichotomisation of response (which in reality occupies a spectrum). In the paper our colleagues discuss, we assessed the relative performance of a number of additional PET-CT metrics in a cohort of patients with oesophageal cancer receiving neoadjuvant chemotherapy. We found that whilst composite spatial-avidity metrics of metabolic tumour response (mTR; such as metabolic or tumour glycolytic volume) appeared to have greater predictive accuracy than avidity alone, this was by no means a perfect surrogate for pathological tumour response (pTR). We noted that the primary tumour and nodal tumour often responded differently, and subsequently found mNR (but not mTR) to be an independent predictor of prognosis, once pTR was considered (1). This makes sense, as logically response of the primary tumour to neoadjuvant therapy is relevant primarily in terms of facilitating a clear (R0) resection, and secondarily as a surrogate of therapy sensitivity of any occult metastases. However, the primary tumour overall may be very different to the metastatic clones responsible for these metastases, in contrast to nodal tumour. We therefore believe that mNR provides valuable surrogate information regarding the phenotype of these metastatic clones, which crucially are responsible for the vast majority of post-operative recurrences.
However, beyond the limitations in our study discussed by our colleagues, we acknowledge mNR to suffer the same failings as mTR: unphysiological thresholding of responses, and not infrequent disagreement between metabolic and pathological response. Further complicating issues are the subjectivity inherent in pTR assessment (8), and whether a homogenous microscopic assessment truly reflects the different phenotypes within a cancer. Indeed, we previously reported a novel concept of genetic response of oesophageal adenocarcinoma to neoadjuvant chemotherapy (as evidenced by next generation sequencing). This was generally concordant with pathological response, but with some notable exceptions suggesting some tumours exhibit a profound response, followed by rapid overgrowth by a marginal clone which was not captured using traditional radiological or pathological response assessment (5).
Ultimately, assessment of these many facets of response in parallel may allow us to quantify response better during therapy (e.g., serial biopsy with molecular assessment of the primary tumour and circulating DNA, along with cross-sectional and functional response using PET-CT). However, until we have the ability to do so, as our colleagues suggest both composite avidity-spatial PET-CT metrics of the primary tumour plus mNR may better be able to direct therapy for patients in clinical trials.
Conflicts of Interest: The authors have no conflicts of interest to declare.
- Findlay JM, Bradley KM, Wang LM, et al. Metabolic nodal response as a prognostic marker after neoadjuvant therapy for oesophageal cancer. Br J Surg 2017;104:408-17. [Crossref] [PubMed]
- Findlay JM, Bradley KM, Wang LM, et al. Predicting pathologic response of esophageal cancer to neoadjuvant chemotherapy: the implications of metabolic nodal response for personalized therapy. J Nucl Med 2017;58:266-75. [Crossref] [PubMed]
- Sjoquist KM, Burmeister BH, Smithers BM, et al. Survival after neoadjuvant chemotherapy or chemoradiotherapy for resectable oesophageal carcinoma: an updated meta-analysis. Lancet Oncol 2011;12:681-92. [Crossref] [PubMed]
- Morgan G, Aftimos P, Awada A. Current-day precision oncology: from cancer prevention, screening, drug development, and treatment - have we fallen short of the promise? Curr Opin Oncol 2016;28:441-6. [Crossref] [PubMed]
- Findlay JM, Castro-Giner F, Makino S, et al. Differential clonal evolution in oesophageal cancers in response to neo-adjuvant chemotherapy. Nat Commun 2016;7:11111. [Crossref] [PubMed]
- Findlay JM, Middleton MR, Tomlinson I. A systematic review and meta-analysis of somatic and germline DNA sequence biomarkers of esophageal cancer survival, therapy response and stage. Ann Oncol 2015;26:624-44. [Crossref] [PubMed]
- Lordick F, Ott K, Krause BJ, et al. PET to assess early metabolic response and to guide treatment of adenocarcinoma of the oesophagogastric junction: the MUNICON phase II trial. Lancet Oncol 2007;8:797-805. [Crossref] [PubMed]
- MacGregor TP, Maughan TS, Sharma RA. Pathological grading of regression following neoadjuvant chemoradiation therapy: the clinical need is now. J Clin Pathol 2012;65:867-71. [Crossref] [PubMed]